20230331IRP Vol 2.pdf

2023 Integrated Resource Plan
Volume II March 31, 2023
RECEIVED
2023 March, 31 3:49PM
IDAHO PUBLIC
UTILITIES COMMISSION
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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APPENDIX A – LOAD FORECAST
Introduction
This appendix reviews the load forecast used in the modeling and analysis of the 2023 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 to develop a 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, and lighting customer classes. The classes are
modeled separately using variables specific to their usage patterns. For residential customers,
typical energy uses include space heating, air conditioning, 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 May 2022. The compound annual load growth rate for
the 10-year period (2023 through 2032) is 2.69 percent. Relative to the load forecast prepared for the 2021 IRP, PacifiCorp’s 2032 forecast load requirement increased in Oregon, Utah and Idaho, while PacifiCorp system load requirement increased 17.00 percent in 2032. Figure A.1 has a comparison of the load forecasts from the 2023 IRP to the 2021 IRP.

PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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Figure A.1 – PacifiCorp System Energy Load Forecast Change, at Generation, pre-DSM

Table A.1 and Table A.2 show the annual load and coincident peak load forecast when not reducing load projections to account for new energy efficiency measures.1 Tables A.3 and A.4 show the forecast changes relative to the 2021 IRP load forecast for loads and coincident system peak, respectively.
Table A.1 – Forecasted Annual Load, 2023 through 2032 (Megawatt-hours), at Generation, pre-DSM
2023 64,032,930 16,209,670 4,638,720 863,330 28,599,180 9,644,200 4,077,830
2024
2025 69,805,060 19,730,320 4,700,760 855,220 30,361,220 10,074,860 4,082,680
2026
2027 72,649,770 21,761,290 4,756,830 853,180 31,034,420 10,116,940 4,127,110
2028
2029 77,919,280 23,952,780 4,841,310 855,160 33,861,360 10,239,970 4,168,700
2030
2031 80,380,690 24,821,690 4,930,700 856,600 35,199,890 10,364,120 4,207,690
2032 81,321,780 25,160,880 4,990,400 859,960 35,600,350 10,476,730 4,233,460
Compound Annual Growth Rate
2023-32 2.69% 5.01% 0.82% -0.04% 2.46% 0.92% 0.42%

1 Energy efficiency load reductions are included as resources in the Plexos model.
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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Table A.2 – Forecasted Annual Coincident Peak Load (Megawatts) at Generation, pre-DSM
11,033 2,650 835 147 5,408 1,221 772
2024
2025 11,747 3,011 857 148 5,628 1,301 803
2026
2027 12,051 3,188 887 150 5,707 1,306 813
2028
2029 12,683 3,487 926 156 6,023 1,292 798
2030
2031 13,123 3,631 966 160 6,214 1,311 841
2032 13,209 3,632 985 161 6,268 1,316 847
Compound Annual Growth Rate
2023-32 2.02% 3.56% 1.86% 1.03% 1.65% 0.83% 1.03%

Table A.3 – Annual Load Change: May 2022 Forecast less June 2022 Forecast (Megawatt-hours) at Generation, pre-DSM
2023 789,940 450,990 (17,310) (19,170) 388,800 (112,270) 98,900
2024 3,047,960 2,268,330 (18,530) (26,610) 947,850 (199,700) 76,620
2025
2026 5,411,390 4,038,830 (39,130) (38,160) 1,334,560 33,730 81,560
2027
2028 10,597,700 6,589,320 (39,200) (39,800) 3,990,880 1,290 95,210
2029
2030 11,088,630 6,798,020 (37,750) (42,820) 4,328,150 (61,120) 104,150
2031
2032 11,814,570 7,448,410 (22,820) (43,290) 4,388,360 (85,440) 129,350

Table A.4 – Annual Coincident Peak Change: May 2022 Forecast less June 2022 Forecast
(Megawatts) at Generation, pre-DSM
342 188 46 5 154 (58) 7
2024 620 353 50 6 211 (5) 5
2025
2026 891 540 61 7 264 (10) 29
2027
2028 1,441 784 82 8 568 (12) 12
2029
2030 1,577 945 108 16 538 (47) 17
2031
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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2032 1,807 1,077 133 19 572 (49) 56

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 90 counties. The level of retail sales for each state and
county is correlated with economic conditions and population statistics in each state. PacifiCorp uses both economic data, such as employment, and population data, to forecast its retail sales. Looking at historical sales and employment data for PacifiCorp’s service territory, 2000 through 2021, in Figure A.2, it is apparent that the Company’s retail sales are correlated to economic conditions in its service territory, and most recently the economic downturn and rebound from the
COVID-19 pandemic.
Figure A.2 – PacifiCorp Annual Retail Sales 2000 through 2021 and Western Region Employment
The 2023 IRP forecast utilizes the March 2022 release of IHS Markit economic driver forecast;
whereas the 2021 IRP relied on the October 2019 release from IHS Markit. Figure A.3 shows the
weather normalized average system residential use per customer.

PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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Figure A.3 – PacifiCorp Annual Residential Use per Customer 2001 through 2021

Weather

The Company’s load forecast is based on historical actual weather adjusted for expectations and impacts from climate change. The historical weather is defined by the 20-year period of 2002 through 2021. The climate change weather uses the data from the historical period and adjusts the percentile of the data to achieve the expected target average annual temperature and calculate the
HDD and CDD impacts and peak producing weather impacts within the energy forecast and peak
forecast, respectively. The climate change weather target temperature relies on actual 1990 average temperatures and projected temperature increases over 1990 average temperatures as determined by the United
States Bureau of Reclamation (Reclamation) in the West-Wide Climate Risk Assessments:
Hydroclimate Projections Study (Study).2 The Company determined daily average temperatures and peak producing temperatures that correspond to the midpoint of the projected temperature increase between the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 ranges in the Study.

2 United States Bureau of Reclamation, March 2021, Managing Water in the West, Technical Memorandum No.
ENV-2021-001, West-Wide Climate Risk Assessments: Hydroclimate Projections. https://www.usbr.gov/climate/secure/docs/2021secure/westwidesecurereport1-2.pdf
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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Table A.5 – Projected Range of Temperature Change in the 2020s and 2050s relative to the 1990s3
Bureau of Reclamation Site PacifiCorp Jurisdiction Assumption
Projected Range of Temperature Change (°F)*
Klamath River near Klamath California 1.7 to 2.6 3.6 to 5.2
Snake River Near Heise Idaho 1.6 to 3.0 4.1 to 5.9
Klamath River near Seiad Valley Oregon 1.8 to 2.7 3.7 to 5.3
Green River near Greendale Utah 1.8 to 3.3 4.2 to 6.3
Yakima River at Parker Washington 1.8 to 2.8 3.6 to 5.6
Green River near Greendale Wyoming 1.8 to 3.3 4.2 to 6.3
*Lower bound of temperature projections based on RCP 4.5, while upper bound based on RCP 8.5
In addition to climate change weather discussed above, the Company has reviewed the
appropriateness of using the average weather from a shorter time period as its “normal” peak
weather. Figure A.4 indicates that peak producing weather does not change significantly when comparing five, 10, or 20-year average weather. The Company also updated its temperature spline models to the five-year time period of October
2016 – September 2021. The Company’s spline models are used to model the commercial,
residential and irrigation class temperature sensitivity at varying temperatures.

3 Ibid.
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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Figure A.4 – 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 the 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 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.
The underlying efficiency data is based on estimates of energy efficiency from the US Department of Energy’s Energy Information Administration (EIA). The EIA estimates the efficiency of appliance stocks and the saturation of appliances at the national level and for individual Census Regions.
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
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
(Average Dry Bulb Temperature on Peak Day (Deg
F.))
20 Year Average 10 Year Average 5 Year Average
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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jurisdictions. Customer forecasts are provided by the customer to the Company through a regional business manager (“RBM”).
Actual Load Data
With the exception to the industrial class, the Company uses actual load data from January 2000
through February 2022. The historical data period used to develop the industrial monthly sales forecast is from January 2000 through February 2022 in Utah, Wyoming, and Washington, January 2002 through February 2022 in Idaho, and January 2003 through February 2022 in California and January 2008 through February 2022 in Oregon.

The following tables are the annual actual retail sales, non-coincident peak, and coincident peak by state used in calculating the 2023 IRP retail sales forecast.
Table A.6 – Weather Normalized Jurisdictional Retail Sales 2000 through 2021
Year California Idaho Oregon Utah Washington Wyoming System
2000 770,820 3,116,508 13,850,006 18,970,364 4,084,537 7,411,248 48,203,483
2001 768,864 3,005,141 13,392,332 18,559,167 3,995,989 7,652,997 47,374,489
2002 791,735 3,256,168 12,957,060 18,630,359 3,992,241 7,429,503 47,057,066
2003 812,166 3,269,807 12,939,631 19,281,125 4,041,618 7,426,913 47,771,259
2004 835,515 3,333,624 13,058,719 19,892,658 4,073,666 7,793,618 48,987,800
2005 827,540 3,285,758 13,059,825 20,363,787 4,183,226 7,993,309 49,713,446
2006 848,726 3,346,052 13,774,581 21,187,643 4,108,566 8,209,339 51,474,907
2007 866,742 3,425,039 13,871,720 22,086,852 4,053,437 8,504,273 52,808,062
2008 857,500 3,444,347 13,135,644 22,715,811 4,052,529 9,203,352 53,409,183
2009 819,819 2,979,003 12,970,802 22,146,938 4,024,282 9,256,870 52,197,714
2010 835,326 3,468,573 13,046,266 22,590,597 4,023,412 9,648,267 53,612,440
2011 797,736 3,493,098 12,891,100 23,406,694 3,994,623 9,792,857 54,376,107
2012 776,608 3,543,173 12,902,817 23,692,760 4,017,534 9,469,443 54,402,334
2013 766,445 3,586,627 12,955,649 23,770,781 4,029,058 9,533,401 54,641,961
2014 763,083 3,574,849 13,044,614 24,245,893 4,074,243 9,587,020 55,289,702
2015 732,905 3,532,641 13,044,577 24,008,248 4,064,376 9,360,103 54,742,851
2016 745,142 3,495,674 13,203,510 23,655,727 4,012,667 9,191,271 54,303,991
2017 749,028 3,608,590 13,230,882 23,807,001 4,044,195 9,331,829 54,771,525
2018 733,383 3,641,048 13,190,422 24,586,138 4,030,934 9,243,563 55,425,488
2019 735,995 3,530,085 13,272,614 24,527,670 4,022,640 9,317,139 55,406,143
2020 755,926 3,596,981 13,179,949 24,703,889 4,074,386 8,317,048 54,628,180
2021 787,505 3,534,599 13,698,449 25,272,678 4,108,739 8,494,257 55,896,227
2000-21 0.10% 0.60% -0.05% 1.38% 0.03% 0.65% 0.71%
*System retail sales do not include sales for resale
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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Table A.7 – Non-Coincident Jurisdictional Peak 2000 through 2021
Non-Coincident Peak - Megawatts (MW)*
Year California Idaho Oregon Utah Washington Wyoming System
2000 176 686 2,603 3,684 785 1,061 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
169 722 2,451 4,004 788 1,126 9,260
2004 193 708 2,524 3,862 920 1,111 9,317
2005 189 753 2,721 4,081 844 1,224 9,811
2006 180 723 2,724 4,314 822 1,208 9,970
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
177 770 2,686 4,596 854 1,404 10,486
2012 159 800 2,550 4,732 797 1,337 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
157 843 2,598 5,226 837 1,326 10,986
2016 155 848 2,584 5,018 819 1,300 10,724
2017 177 830 2,920 4,932 943 1,354 11,156
2018 158 830 2,608 5,091 849 1,319 10,854
151 793 2,632 5,158 895 1,363 10,993
2020 155 806 2,562 5,336 848 1,271 10,979
2021 149 771 2,894 5,547 938 1,299 11,598
*Non-coincident peaks do not include sales for resale

Table A.8 – Jurisdictional Contribution to Coincident Peak 2000 through 2021
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
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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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
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
152 805 2,472 5,081 833 1,259 10,601
2016 139 575 2,462 4,940 817 1,201 10,135
2017 152 593 2,547 4,911 787 1,306 10,296
2018 126 741 2,526 5,037 790 1,295 10,514
122 731 2,276 5,158 761 1,248 10,297
2020 127 603 2,428 5,336 839 1,180 10,515
2021 145 767 2,543 5,319 839 1,214 10,827
*Coincident peaks do not include sales for resale

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, 2021.
Forecast Methodology Overview
Demand-side Management Resources in the Load Forecast
PacifiCorp modeled as a resource option to be selected as part of a cost-effective portfolio resource
mix using the Company’s Plexos capacity expansion optimization model. The load forecast used
for IRP portfolio development excluded forecasted load reductions from energy efficiency ; Plexos then determines the amount of energy efficiency —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 energy efficiency supply curves, along with the economic screening
provided by Plexos, determines the cost-effective mix of energy efficiency 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 forecasted number of customers.
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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The customer forecasts are based on a combination of regression analysis and exponential
smoothing techniques using historical data from January 2000 to February 2022. For the residential class, the Company forecasts the number of customers using IHS Markit’s forecast of each state’s population or number of households as the major driver.
The Company uses a differenced model approach in the development of the residential customer
forecast. Rather than directly forecasting the number of customers, the differenced model predicts the monthly change in number of customers. 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. 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.
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 the climate change peak-producing weather discussed above.
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 for the 20-year period 2002 through 2021, 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.
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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.
Electrification Adjustments
The load forecast used for 2023 IRP portfolio development includes the Company’s expectations for transportation electrification based on current and expected electric-vehicle (EV) adoption trends. These projections were incorporated as a post-model adjustment to the residential and commercial sales forecasts.

Vehicle adoption and load impacts vary by state depending on a variety of socioeconomic factors and policies particular to each state. To develop a prospective forecast of EV adoption, PacifiCorp developed a model to assess trends for light-duty EVs and medium-duty EVs. To develop a future EV adoption curve, the Company reviewed three national EV forecasts, each representing varying
degrees of aggressiveness. While these forecasts represent national trends, the adoption curves
themselves can be applied and adapted to state-specific parameters to reflect current market conditions in the state. The Company calibrates each adoption curve source to base inputs from EIA’s Annual Energy Outlook (AEO) projections and estimated historical vehicle actuals. The AEO inputs include estimated shares of battery electric vehicles and plug-in hybrid electric
vehicles as well as light-duty vehicles and light-duty trucks. Each of the national adoption curve
sources is discussed below to help contextualize the various sources reviewed for this plan’s EV adoption forecast. The load forecast also incorporates the Company’s expectations for building electrification
initiatives. In the near-term, building electrification is relatively minor share of load but is expected to grow over time as state and national policies encouraging fuel substitution and electrification become more prevalent. The Company’s building electrification forecast is based on expected fuel shares for space heating and water heating equipment at the end of its useful life and future new construction shares of electric fuel for these end-uses over time. Adoption curves are calibrated to
expected equipment turnover and new construction rates in alignment with assumptions used in the Conservation Potential Assessment. Adoption curves and timing of building electrification is estimated based on the state specific policies or known market trends supporting advancement of building electrification.
The Company continually assesses both transportation and building electrification market trends, policies, and adoptions levels in each state. As these markets evolve, the Company will continue to update forecasts to reflect new trends as they occur.
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 Preferred Portfolio.
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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Table A.9 – System Annual Retail Sales Forecast 2021 through 2032, post-DSM
Residential Commercial Industrial Irrigation Lighting Total
2023 17,361,583 20,978,789 18,760,385 1,472,103 98,858 58,671,719
2024 17,561,027 23,333,643 18,912,628 1,463,717 95,519 61,366,533
2025 17,663,790 24,565,976 19,192,595 1,455,086 92,615 62,970,063
17,860,209 25,344,020 17,755,233 1,449,220 90,685 62,499,366
2027 18,075,462 27,203,257 17,720,663 1,442,125 89,172 64,530,679
2028 18,386,033 30,063,031 17,769,947 1,434,670 88,119 67,741,799
2029 18,633,432 30,372,554 17,700,916 1,426,506 86,618 68,220,026
18,972,662 30,145,257 17,751,969 1,419,207 85,392 68,374,488
2031 19,332,679 30,522,754 17,739,953 1,412,108 84,220 69,091,714
2032 19,852,639 30,155,847 17,782,332 1,403,445 83,419 69,277,682
1.50% 4.11% -0.59% -0.53% -1.87% 1.86%
Residential
The average annual growth of the residential class sales forecast increased from 0.80 percent in the 2021 IRP to 1.50 percent in the 2023 IRP. The number of residential customers across
PacifiCorp’s system is expected to grow at an annual average rate of 1.48 percent, reaching
approximately 2.06 million customers in 2032, with Rocky Mountain Power states adding 1.82 percent per year and Pacific Power states adding 0.92 percent per year.
Commercial
Average annual growth of the commercial class sales forecast increased from 1.04 percent annual average growth in the 2021 IRP to 4.11 percent in the 2023 IRP. The number of commercial
customers across PacifiCorp’s system is expected to grow at an annual average rate of 0.90 percent,
reaching approximately 246,000 customers in 2032, with Rocky Mountain Power states adding 1.18 percent per year and Pacific Power states adding 0.52 percent per year.
Industrial
Average annual growth of the industrial class sales forecast decreased from -0.11 percent annual average growth in the 2021 IRP to -0.59 percent expected annual growth in the 2023 IRP. 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.
State Summaries
Oregon
Table A.10 – Forecasted Retail Sales Growth in Oregon, post-DSM summarizes Oregon state
forecasted retail sales growth by customer class.
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Table A.10 – Forecasted Retail Sales Growth in Oregon, post-DSM
Year Residential Commercial Industrial Irrigation Lighting Total
2023 5,776,140 6,971,569 1,458,214 270,754 29,920 14,506,597
2024 5,813,544 8,727,403 1,466,594 270,264 29,236 16,307,041
2025 5,806,005 9,761,216 1,495,283 269,413 28,514 17,360,433
2026 5,840,308 10,246,092 1,489,796 269,210 28,009 17,873,416
2027 5,887,124 11,251,088 1,475,161 268,963 27,619 18,909,955
2028 5,974,783 12,561,821 1,461,575 268,836 27,405 20,294,420
2029 6,054,951 12,820,090 1,455,444 268,381 27,108 20,625,973
2030 6,172,566 12,677,326 1,453,566 268,029 26,950 20,598,436
2031 6,314,070 13,084,453 1,459,414 267,642 26,835 21,152,414
2032 6,495,531 13,089,511 1,476,758 267,370 26,832 21,356,002
2023-32 1.31% 7.25% 0.14% -0.14% -1.20% 4.39%
Washington
Table A.11 – Forecasted Retail Sales Growth in Washington, post-DSM summarizes Washington state forecasted retail sales growth by customer class. Table A.11 – Forecasted Retail Sales Growth in Washington, post-DSM
Year Residential Commercial Industrial Irrigation Lighting Total
2023 1,569,912 1,569,506 828,111 161,366 3,294 4,132,188
2024 1,575,457 1,581,008 825,124 159,738 3,231 4,144,559
2025 1,566,405 1,568,866 812,588 158,750 3,199 4,109,809
2026 1,566,847 1,564,706 802,531 158,297 3,192 4,095,573
2027 1,567,629 1,565,138 796,393 157,806 3,190 4,090,156
2028 1,575,315 1,567,825 794,158 157,247 3,200 4,097,744
2029 1,574,971 1,559,991 789,614 156,835 3,190 4,084,601
2030 1,580,219 1,556,026 787,560 156,474 3,190 4,083,470
2031 1,585,479 1,555,833 787,983 156,415 3,190 4,088,900
2032 1,596,353 1,556,759 788,347 156,000 3,199 4,100,658
2023-32 0.19% -0.09% -0.55% -0.38% -0.32% -0.09%

PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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California
Table A.12 - Forecasted Retail Sales Growth in California, post-DSM summarizes California state
forecasted sales growth by customer class.
Table A.6 - Forecasted Retail Sales Growth in California, post-DSM
Year Residential Commercial Industrial Irrigation Lighting Total
2023 377,233 238,946 54,997 97,232 1,628 770,037
2024 377,131 237,264 53,389 96,630 1,600 766,014
374,277 233,240 52,235 96,229 1,569 757,549
2026 372,480 230,331 51,812 96,016 1,549 752,188
2027 370,942 228,808 51,440 95,783 1,534 748,507
2028 370,818 227,945 51,185 95,583 1,527 747,058
2029 368,319 225,742 50,735 95,268 1,515 741,578
2030 366,926 224,681 50,478 95,019 1,509 738,613
2031 365,606 223,441 50,232 94,649 1,504 735,432
365,968 223,270 50,189 94,220 1,506 735,153
Compound Annual Growth Rate
2023-32 -0.34% -0.75% -1.01% -0.35% -0.86% -0.51%
Utah
Table A.13 – Forecasted Retail Sales Growth in Utah, post-DSM summarizes Utah state forecasted
sales growth by customer class.
Table A.7 – Forecasted Retail Sales Growth in Utah, post-DSM
Year Residential Commercial Industrial Irrigation Lighting Total
2023 7,835,131 10,246,229 8,137,068 233,429 49,506 26,501,364
7,986,696 10,832,402 8,238,305 230,300 47,036 27,334,739
2025 8,119,480 11,064,958 8,233,901 227,009 45,163 27,690,511
2026 8,284,098 11,384,983 6,807,862 223,609 44,067 26,744,620
2027 8,454,824 12,261,214 6,827,830 219,645 43,400 27,806,913
2028 8,665,353 13,820,108 6,843,943 215,282 43,126 29,587,812
8,844,710 13,908,034 6,817,082 210,766 42,770 29,823,362
2030 9,066,276 13,850,077 6,834,566 206,189 42,633 29,999,741
2031 9,287,214 13,845,537 6,834,089 201,514 42,554 30,210,908
2032 9,613,627 13,483,845 6,814,215 195,865 42,630 30,150,181
2023-32 2.30% 3.10% -1.95% -1.93% -1.65% 1.44%

PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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Idaho
Table A.14 - Forecasted Retail Sales Growth in Idaho, post-DSM summarizes Idaho state forecasted sales growth by customer class.
Table A.8 - Forecasted Retail Sales Growth in Idaho, post-DSM
Residential Commercial Industrial Irrigation Lighting Total
2023 793,909 551,520 1,770,789 679,642 2,641 3,798,500
2024 804,094 554,572 1,736,293 677,301 2,625 3,774,885
2025 806,682 552,218 1,736,660 674,431 2,594 3,772,585
811,343 549,260 1,735,986 672,973 2,571 3,772,133
2027 815,138 545,183 1,734,061 670,967 2,547 3,767,897
2028 820,769 542,345 1,732,080 668,926 2,531 3,766,652
2029 819,247 534,579 1,728,504 666,588 2,502 3,751,419
820,297 527,445 1,726,072 664,917 2,480 3,741,211
2031 820,173 519,098 1,724,099 663,366 2,460 3,729,196
2032 823,076 514,464 1,722,624 661,563 2,447 3,724,174

Wyoming
Table A.15 – Forecasted Retail Sales Growth in Wyoming, post-DSM summarizes Wyoming state
forecasted sales growth by customer class.
Table A.9 – Forecasted Retail Sales Growth in Wyoming, post-DSM
Year Residential Commercial Industrial Irrigation Lighting Total
2023 1,009,258 1,401,020 6,511,205 29,679 11,870 8,963,032
2024 1,004,104 1,400,993 6,592,922 29,485 11,791 9,039,295
990,941 1,385,479 6,861,929 29,252 11,575 9,279,176
2026 985,132 1,368,647 6,867,245 29,115 11,297 9,261,436
2027 979,805 1,351,827 6,835,777 28,961 10,882 9,207,251
2028 978,994 1,342,988 6,887,006 28,797 10,329 9,248,113
971,235 1,324,118 6,859,538 28,668 9,534 9,193,092
2030 966,378 1,309,701 6,899,728 28,579 8,631 9,213,017
2031 960,137 1,294,392 6,884,136 28,522 7,676 9,174,863
2032 958,085 1,287,998 6,930,199 28,427 6,805 9,211,514
2023-32 -0.58% -0.93% 0.70% -0.48% -5.99% 0.30%
PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST
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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 varying temperatures and economic conditions.
The May 2022 forecast is the baseline scenario. For the high and low load growth scenarios,
optimistic and pessimistic economic driver assumptions from IHS Markit were applied to the economic drivers in the Company’s load forecasting models. These growth assumptions were extended for the entire forecast horizon. Further, the high and low load growth scenarios also incorporate the standard error bands for the energy and the peak forecast to determine a 95%
prediction interval around the base IRP forecast. Lastly, the high scenario incorporates the
Company’s low private generation forecast, while the low scenario incorporates the high private generation forecast. The 95% prediction interval is calculated at the system level and then allocated to each state and
class based on their contribution to the variability of the system level forecast. The standard error
bands for the jurisdictional peak forecasts were calculated in a similar manner. The final high load growth scenario includes the optimistic economic forecast and low private generation forecast plus the monthly energy adder and the monthly peak forecast with the peak adder. The final low load growth scenario includes the pessimistic economic forecast and high private generation forecast
minus the monthly energy adder and monthly peak forecast minus the peak adder.
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.

The 20-year normal scenario is based on normal weather, which is defined by the 20-year time period of 2002 through 2021 (50th percentile). In prior IRP cycles, this scenario is what was traditionally used as the base IRP load forecast.
Figure A.5 shows the comparison of the above scenarios relative to the Base Case scenario.

PACIFICORP – 2023 IRP APPENDIX A – LOAD FORECAST

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Figure A.5 – Load Forecast Scenarios, pre-DSM

-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
Me
g
a
w
a
t
t

(
M
W
)
1-in-20 Weather 20-Year Normal High Base Case Low
PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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APPENDIX B - REGULATORY COMPLIANCE

This appendix describes how PacifiCorp’s 2023 Integrated Resource Plan (IRP) complies with (1) the various state commission IRP standards and guidelines, (2) specific analytical requirements
stemming from acknowledgment orders for the company’s 2021 Integrated Resource Plan, and
other ongoing IRP acknowledgement order requirements as applicable, 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.33 ● Table B.2 - Provides a description of how PacifiCorp addressed the 2021 IRP acknowledgement order 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 Transportation Commission IRP rules issued in December 2020
in WAC 480-100-620. ● 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.

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 from 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 serves to inform all parties on the planning issues and approach. The public input process for this IRP will be described in Volume I, Chapter 2 (Introduction), as well as Volume II, Appendix C (Public) Input fully complies with IRP standards and guidelines.

33 California Public Utilities Code Section 454.5 allows utility with less than 500,000 customers in the state to request an exemption 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.
Introduction
General Compliance
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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 load 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
options, as required by state commission rules. These resource options include supply-side,
demand-side, and transmission alternatives. The evaluation of the alternatives in the IRP, as detailed in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (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 8 – Modeling and Portfolio Evaluation. 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 carbon dioxide (CO2) emissions. This portfolio analysis and the results and conclusions drawn from the analysis are described in Volume I, Chapter 9 (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 10 (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 2021 IRP.
The 2023 IRP and related Action Plan are filed with each commission with a request for acknowledgment or acceptance, as applicable. Acknowledgment or acceptance means that a
commission recognizes the IRP as meeting all regulatory requirements at the time of
acknowledgment. In a case where a commission acknowledges the IRP in part or not at all, PacifiCorp may modify and seek to re-file an IRP that meets their acknowledgment standards or address any deficiencies in the next plan.
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.
PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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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 (Docket R.16-02-007).
Decision (D.) 18-02-018 instructed PacifiCorp to file an alternative IRP consisting of any IRP submitted to another public regulatory entity within the previous calendar year (Alternative Type 2 Load Serving Entity Plan). D.18-02-018 also instructed PacifiCorp to provide an adequate
description of treatment of disadvantaged communities, as well as a description of how planned
future procurement is consistent with the 2030 Greenhouse Gas Benchmark. PacifiCorp also provides its IRP and an IRP Supplement in lieu of providing a Renewables Portfolio Standard Procurement Plan, as authorized by Public Utilities Code Section 399.17(d).
Requirements for PacifiCorp’s IRP Supplement are outlined in an annual Assigned
Commissioner’s Ruling from the CPUC1 and D.22-12-030 issued on December 19, 2022, approving the company’s 2021 IRP Supplement (2022 Off-Year Supplement to its 2021 IRP). On October 18, 2019, PacifiCorp submitted its 2019 IRP in compliance with D.18-02-018.

On April 6, 2020, the CPUC issued D.20-03-028, which reiterated PacifiCorp’s ability to file an alternative IRP. On September 1, 2021, PacifiCorp filed its 2021 IRP in Docket R.18-07-003 in compliance with
D.08-05-029.
On November 1, 2022, PacifiCorp filed its 2021 IRP in Docket R.20-05-003 in compliance with D.18-02-018, D.20-03-028, and D.22-02-004.
On January 18, 2023, PacifiCorp filed its 2021 IRP Supplement (2022 Off-Year Supplement to its
2021 IRP) in Docket R.18-07-003 in compliance with D.08-05-029 and D.22-12-030. Idaho
The Idaho Public Utilities Commission’s (Idaho PUC) Order No. 22299, issued in January 1989, specifies integrated resource planning requirements. This 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)

1 The most recent Assigned Commissioner’s Ruling is the Assigned Commissioner and Assigned Administrative Law Judge’s Ruling Identifying issues and Schedules of Review for 2022 Renewables Portfolio Standard Procurement Plans and Denying Joint IOU’s Motion to File Advice Letters for Market Offer Process¸ Rulemaking 18-07-003 (April 11, 2022).
PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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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 2023, and fully addresses the above report components. Oregon

This IRP is submitted to the Oregon Public Utility Commission (OPUC) in compliance with its planning guidelines issued in January 2007 (Order No. 07-002). The Oregon PUC’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. 12-013 ). Consistent with the earlier guidelines (Order 89-
5072), the Oregon PUC notes that acknowledgment does not guarantee favorable ratemaking treatment, only that the plan seems reasonable at the time acknowledgment is given. Table B 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 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 a two-year progress report of the previously filed plan, which was the Company’s 2021 IRP (Washington Administrative Code 480-100-625) (effective,
December 2020).
In its report, the rule requires PacifiCorp to include an update of its load forecast; demand-side resource assessment, including new conservation potential assessment; resource costs; and the portfolio analysis and preferred portfolio. The report must also include other updates that are
necessary due to changing state or federal requirements, or significant changes to economic or
market forces; and an update for any elements found in the Company’s current Clean Energy Implementation Plan (CEIP). Please refer to Appendix O (Washington Two-year Progress Report Additional Elements) for additional detail regarding updates to elements of the Company’s CEIP. Wyoming
Wyoming Public Service Commission issued new rules that replaced the previous set of rules on
2 Public Utility Commission of Oregon, Order No. 12-013, Docket No. 1461, January 19, 2012.
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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.1 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.
PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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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.
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).
Commission General Order R-601 further adopted IRP rules compliant with CETA.
Electric Utility
Conservation Standards and Practices January 1989.
and Water Utilities, Chapter 3, Section 33, March 21, 2016.
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.
Filing Requirements

PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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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.
by the commission, each electric utility must file an integrated resource plan (IRP) with the commission by January 1, 2021, and every four years thereafter.
At least every two years after the utility files its IRP, beginning January 1, 2023, the utility must file a two-year progress report.
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.
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.
Note, however, that Rate
Plan legislation allows pre-approval of near-term
resource investments.

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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 Oregon PUC 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.
WUTC 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 15 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 Commission of Wyoming, 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, environmental risks, and equitable distribution of benefits 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.
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utilities must develop a ten-year clean energy action plan for implementing RCW 19.405.030 through 19.405.050.
Elements
• 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.
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.
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
• All resources evaluated on a consistent and
• Risk and uncertainty must be considered.
• The primary goal must
be least cost, consistent with the long-run
• The plan must be consistent with Oregon and federal energy
• 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-
• Construction of resource portfolios
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uncertainties.
• Portfolio analysis shall include fuel transportation and transmission requirements.
• Plan includes conservation potential study, demand response resources, environmental costs, and distributed generation technologies.
• Avoided cost filing required within 30 days of acknowledgment.
• evaluation of energy supply resources (including transmission and distribution) and improvements in conservation using “lowest reasonable cost” criteria.
• An assessment and determination of resource adequacy metrics.
• An assessment of energy and nonenergy benefits and reductions of burdens to vulnerable populations and highly impacted communities; long-term and short- term public health and environmental benefits, costs, and risks; and energy security risk
• 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
• Must develop a ten-year clean energy action plan for implementing RCW 19.405.030 through 19.405.050.
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• summary of substantive changes to modeling methodologies or inputs that result in changes to the utility's resource need, as compared to the utility's previous IRP.
• The IRP must include an analysis and summary of the avoided cost estimate for energy, capacity, transmission, distribution, and greenhouse gas emissions costs. The utility must list nonenergy costs and benefits addressed in the IRP and should specify if they accrue to the utility, customers, participants, vulnerable populations, highly impacted communities, or the general public.
• The utility must provide a summary of public comments received during the development of its IRP and the utility's responses, including whether issues raised in the comments were addressed and incorporated into the

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documentation of the reasons for rejecting any public input

PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
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Table B.2 – Handling of 2021 IRP Acknowledgment and Other IRP Requirements
Reference IRP Requirement or Recommendation How the Guideline is Addressed in the
2023 IRP
Idaho
Order No. 35514 p. 17

IRP, to clarify whether a LOLH reliability target of 2.4 hours per year was achieved by the Company’s
of FOT availability limits.
Company has not performed detailed hourly stochastic analysis so as to precisely determine the reliability of each of its portfolios. For reference, due to the complexity of the Company’s portfolio and system operations, running one year of one study through 50 iterations could take a single computer a week. The Company’s reliability assessment is intended to ensure that each portfolio achieves a comparable level of reliability. Because each study measures availability against requirements in every hour during the reliability assessment, portfolios will logically achieve comparable reliability. Further, ENS measures support that this is the case. Discussion of the Company’s FOT availability limits is provided in Chapter 5
date for purposes of PURPA avoided cost rates and whether the inclusion of three percent contingency amounts for firm purchases were appropriate to include to meet Company load.
years is provided in Chapter 5 (Reliability and Resiliency)the Company pursues sufficient resources to reduce market reliance of the 20-year planning period. In actual operations, PacifiCorp must balance the risk of higher reliance on market purchases against the cost of procuring from a limited pool of resource options available in the very near term, rather than from a larger pool of resource options available in the next few years. That balancing will be a key consideration in PacifiCorp’s ongoing 2022 All-Source Request for Proposals. As a result, forthcoming developments may be more pertinent to the question of deficit dates than the 2023 IRP itself. As detailed in Volume II, Appendix F (Flexible Reserve Study), to the extent the PacifiCorp’s firm market purchases come from balancing authority areas, those entities will the contingency reserve obligation on the generation used to support the sale, and PacifiCorp’s contingency reserve obligation will be reduced relative to what it would have been had it used its own generation to serve that
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realities of natural gas, we encourage the Company to continue exploring an
of cost-effective natural gas resources in a portfolio.
options per the supply-side resource table as developed throughout the public input meeting process. New gas options were not selected in the least-cost, least-risk methodology to develop the final preferred portfolio. PacifiCorp recognizes that many non-emitting technologies require technological progress to achieve the capabilities and costs assumed in the 2023 IRP, and will continue to consider technologies that are presently available. Because the Inflation Reduction Act provides tax credits only for non-emitting resources, gradually transitioning a new resource to a non-emitting fuel comes at a significant cost. See Volume I, Chapter 7
complexities with the Natrium project and direct the Company to continue to assess the risks of technology viability and potential delays with Natrium and plan accordingly.
online in the summer of 2030. The 2023 IRP includes two “no nuclear” variant studies as
alternative path analysis and potential costs and benefits. PacifiCorp continues to evaluate resources within the context of an evolving
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Reference IRP Requirement or Recommendation How the Guideline is Addressed in the 2023 IRP
Oregon
Order No. 22-178, p. 7 Require PacifiCorp to perform
additional and more varied analyses regarding Jim Bridger
Units 3 and 4, including a no minimum take analysis as
and an analysis of endogenous
retirement dates frequent enough to approximately match Staffs
suggestion of allowing for retirement every two years.
available year. As communicated during the 2023 public input meeting series and in response to
feedback, no minimum take assumptions were assumed in Plexos modeling beyond present
contracts. For Jim Bridger 3 and 4 this means the complete removal of minimum take provisions.
updated long-term fuel plan for Jim Bridger with its 2023 IRP. PacifiCorp’s request for an extension of time to submit the updated long-term fuel plan for Jim Bridger on May 31, 2023.
PacifiCorp has a complete and balanced portfolio given the current posture of the Natrium project.
the summer of 2030. The 2023 IRP includes two “no nuclear” variant studies as described in Volume I, Chapters 8 and 9, designed to inform alternative path analysis and potential costs and benefits. PacifiCorp continues to evaluate nuclear resources within the context of an evolving planning environment.
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PacifiCorp to articulate clearer justifications for its transmission projects, including how the company assessed transmission needs and alternatives comprehensively, how and why a
transmission planning process, why it is reasonable to pay substantial costs for these particular projects, and what quantifiable (and quantified) and non-quantifiable (but valued qualitatively) benefits will come to Oregon ratepayers in particular and PacifiCorp ratepayers in general, as comfrom regional projects that accrue to other regional actors not
options based on the three cluster study outcomes completed thus far, as well as other analysis for locations not well-represented in the cluster study process. This represents the best available information regarding potential costs and resources. The addition of surplus and flexible hybrid resource options specifically allows the model to avoid transmission costs while increasing net generating capability at a given location using proportions of different technologies that are appropriate to a location and the needs of the portfolio as a whole. These options were modeled endogenously and in competitin multiple public input meetings. See Volume I, Chapter 4 (Transmission), and Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
produce the full cost information for the [transmission] projects we acknowledge today in the rate
into rate base.
its rate case proceedings. For the 2023 IRP, scost information is provided in Volume I, Chapter 1 (Executive Summary), and expanded cost information is provided in workpapers.
to the grid, it is critical not only that transmission be built, but that the Commission and stakeholders need to have sufficient information to verify that ratepayers are getting the benefits they are paying for at each stage of development. Going forward, we expect PacifiCorp to provide information that allows that assessment at the outset. We also expect the company to actively encourage key stakeholders like Commission Staff and consumer advocates to participate and provide a larger window into its own transmission planning processes.
transfer capability and resource enabled by transmission options. Options are modeled endogenously, and selections are driven primarily by
system transfer and to serve load. In the 2023 IRP, costs, descriptions, and transfer capabilities are defined, and in addition near-rooted in cluster study and queue analysis and
transmission costs to be avoided where appropriate. The transmission option modeling strategy was discussed at three public input meetings spanning June 2022 through February 2023 with opportunities for feedback and recommendations. Also, modeling of scale renewable resources for Oregon’s CEP assumes there are no accompanying transmission requirements, providing an additional opportunity to evaluate transmission avoidance beyond the native core functionality of the Plexos model. See Chapter 4 (Transmission), and Volume I, Chapter 8
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37
likely QF contract renewal rate. Because PacifiCorp operates in a multi-state footprint, we understand this assessment to be more complicated than an Oregononly renewal rate. However, PacifiCorp should use historical renewable rates as well as other relevant information in its
forecast as accurate as possible.
establish a 79% renewal rate, which was implemented in the 2023 IRP and presented at the September 1-2, 2022 public input meeting. The analysis can be viewed at this web link: https://www.pacificorp.com/content/dam/pcorp/documents/en/pacificorp/energy/integrated-resource-plan/2023-irp/QF_Extension_History_2012-2017-2022.xlsx. For the purpose of modeling in the 2023 IRP, each QF was assumed to have a 79% chance of renewing, so it is reduced to 79% of its current size upon reaching its current expiration date and then continues indefinitely.
Appx B p. 1 for large, flexible loads such as hydrogen electrolysis within the 2023 IRP. The parameters of the study would be further discussed in the 2023 IRP process. Such a sensitivity would consider optimal locations and years to include large amounts of highly flexible load, throughout the planning timeframe. We adopt
there may be additional large loads, such as data centers, that fall under this recommendation too.
Potential Evaluation) for analysis of potential hydrogen electrolysis load opportunities. PacifiCorp would note that with expected transmission builds and the sizeable quantity of energy storage on its system in the preferred portfolio, the difference in marginal prices by location is relatively smallco-locating hydrogen electrolysis with renewable generation may have some benefits, it may be outweighed by the costs of transporting hydrogen to end users. In addition, the potential for flexible load is also represented in part through stochastic load variation and through seven load-related sensitivitiesIn addition to the 2023 IRP’s four core load sensitivities (High load, Low Load, 1 in 20 Load and 20-year Normal Load) and two load-related sensitivities (High Private generation and Low Private Generation), PacifiCorp has also added a “New Load” sensitivity which contemplates an unanticipated large load addition to understand the impacts of such an occurrence. See Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results). PacifiCorp continues to evaluate how to usefully
Appx B p. 1 stakeholder process to determine what source the cost data in the 2023 IRP will rely on.
at a workshop held on September 2, 2022 as part of its public input process. In addition, stakeholders participated in the decision to model offshore wind and associated transmission on a linear basis where any amount of a 1000 MW project could be selected assuming PacifiCorp could participate in partnership with other utilities. The decision was also made to allow other resources to compete for usage of the land-based transmission system upgrades necessary to enable offshore wind. An offshore wind counterfactual study was also run to determine the magnitude of the costs and benefits of offshore wind.
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Appx B p. 1 the company's local transmission planning process as appropriate and to request that sufficient information to inform consideration of offshore wind in future IRPs is made available in
(“ESR”), submitted by the Oregon Public Utility Commission (“OPUC”) Staff March 2022 to have PacifiCorp evaluate the effects of 1.0 GW of Offshore Wind (OSW) generation in southern
Del Norte substation located in Del Norte, California.
Appx B p. 2 IRP public workshop series. PacifiCorp will perform a variety of analyses regarding pumped storage hydro … including a careful comparison with other possible pumped storage hydro projects, in the 2023 IRP … [and]
conclude that PacifiCorp has
own in this process.
resource locations across the system. All seven use identical cost and size characteristics appropriate for proxy modeling, and cover at minimum four projects unassociated with PacifiCorp. As modeled, none of the projects are actual, and the Company is not modeling its own projects. Instead, the 2023 IRP represents pumped hydro storage as proxy resources. Every endogenous model run considers the selection of any or all of these resources among the multitude of competing options. Whether selected or not, pumped hydro projects are eligible to bid into PacifiCorp’s all-
agnostic modeling of actual bids, potentially both
Appx B p. 2 inconsistencies between the WRAP and the approach the IRP
by PacifiCorp.
uses a series of Effective Load Carrying Capability (ELCC) analyses to identify the aggregate capacity contribution of wind, solar, and run-of-river hydro. Attribution of capacity to individual resources is based, in part, on a resource’s generation during the
the remaining load is highest after subtracting out wind and solar generation. The WRAP also uses a five-hour duration for determining the capacity contribution of energy-limited resources, like batteries. A five-hour or longer duration storage resource receives a 100% contribution, while shorter
a one-hour storage has a 20% contribution, while four-hour storage has an 80% contribution. There is significant uncertainty about storage duration requirements and they are necessarily portfolio dependent, so the WRAP will update its capacity contribution calculations each year. PacifiCorp does not have the detailed information about WRAP participants to perform the same calculations over the IRP study horizon. Instead, Volume I, Chapter 6 (Load and Resource Balance) presents portfolio contributions to capacity for PacifiCorp’s 2023 IRP with capacity
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39
the WRAP design. Because ELCC analyses require very data intensive studies with long run times, they have not been performed for the 2023 IRP load and resource reporting across the 20-year IRP horizon. Instead, the remaining capacity between the net load peak and the coincident peak, including the planning reserve margin was allocated among those resources with generation during the top 5 percent load hours that exceeded that during the top 5 percent net load hours. In addition to the above, PacifiCorp used the five-hour duration assumption from the WRAP for energy-limited resources at the start of the IRP planning horizon, but increased the required duration as more energy storage resources were added to the preferred portfolio, which emulates the likely outcomes in the WRAP.
Administrative Hearings Division will lead … a increasing efficiency and demand response, including the consideration of a new, or updated, risk-reduction credit to efficiency.
workshop and plans to participate as more details are known.
Appx B p. 2 PacifiCorp's plan to include peak time rebates in the 2023 CPA. If peak time rebates are determined to be cost-effective, PacifiCorp should further include an exploration of the potential to use a third-party vendor to implement a peak time rebate in advance of the new billing system implementation, in comparison to an approach that waits until the new billing system is implemented, as part of its 2023 IRP.
peak time rebate that would use the Company pre-existing billing system would be premature and duplicative at this time, because the Company is
While AMa peak time rebate program, an advanced billing
capable of accurately billing customers on peak time rebate. Fortunately, the new billing system the Company is planning to deploy would be able to process a peak time rebate program with some minor changes and would be in service on or around 2025. PacifiCorp did assess the potential costs and benefits of peak time rebates in the CPA to inform future determinations and considerations
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17; Appx B p. 3 developer intervenors, upon request, to determine a subset of the confidential data supporting the 2023 IRP that commercially sensitive information that can be provided. The subset would not necessarily need to include all confidential data that is not commercially sensitive. Require PacifiCorp to seek to balance developer intervenors' need for information as IRP stakeholders with PacifiCorp's need to protect commercially sensitive information and keep the data management workload to a
associations that represent developers and developer stakeholders that participated in the Company’s 2021 IRP proceeding, docket LC 77. The first meeting occurred on November 8, 2022 and a follow up meeting was held on March 20, 2023. As a result of these meetings, PacifiCorp restructured its workpapreporting format that will allow a greater amount of information to be public. It will also designate commercially sensitive information as highly confidential; thus, ensuring developers will have access to all confidential information, not just a subset.
least one workshop on equity and justice issues related to the generation transition in its 2023 IRP, and we will ask members of our staff with expertise on these issues to participate. We recognize PacifiCorp’s relationship to employees and to the communities where its resources are located and
how consideration of both factor into planning processes.
Justice Workshop” on September 2, 2022. Topics included community action, promotion and organization of resources, employee transition plan and transition program, and current actions. The company has also held 14 CBIAG meetings since October 27, 2022.
Appx B p. 1 in the 2023 IRP that reflects accurate IRP modeling assumptions. We adopt this recommendation, though we note that we believe PacifiCorp has
with this principle.
providing timely and comprehensive modeling outcomes, which have been included in the 2023 IRP and the preferred portfolio respectively.
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41
storage costs in the Supply Side Table to be in line with the most recent National Renewal Energy Laboratory Annual Technology Baseline report and most recent RFP Final Shortlist. Our understanding is that Staff’s recommendation reflects a preference from stakeholders for
Staff also acknowledges the relevance of the market information obtainable from the most recent RFP. We thus adopt Staff’s recommendation to the extent that it requires the use of publicly available data as well as proprietary sources, but with the understanding that discrepancies
Public Input Meeting.
Appx B p. 1 resources in the IRP Executive Summary, which PacifiCorp agrees to do.
map provided in Appendix I (Capacity Expansion Results).
19; Appx B p. 2 reliability limitations of the LT capacity expansion model and how the IRP team selected the reliability resources of change. PacifiCorp made a strong effort at explanation in this IRP, but that the company should seek to understand questions that remain
accordingly.
year IRP horizon and all possible resource additions and retirements. With PacifiCorp’s system and resource options, this is a lot of possibilities and the model cannot evaluate every hour, let alone maintain the chronological links necessary to consider all likely combinations of load, wind, and solar while enforcing energy storage duration limits, emissions constraints, and thermal unit cycling restrictions. As a result more granular analysis withnecessary to identify the extent that reliability, environmental compliance, and economics are addressed. Discussion of reliability resources
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Appx B p. 2 with the 2023 IRP data discs: A list of the resources that were considered as reliability resources; A list of the reliability resources that were selected in each portfolio, sensitivity, and variant; A clearly marked set of hourly reliability (ENS) data that the
and size of reliability resources to add to each portfolio, sensitivity, variant; and Any metric the Company used to select reliability resources in each
resources for selection based on their value to the system. Workpapers will be provided for each case indicating portfolio changes and for each case indicating hourly unserved energy and reserve shortfalls. These workpapers identify the specific hours in which shortfalls occurred within each year. From the hourly shortfall data, the Company identified the largest consecutive blocks of shortfalls, including the month and hours of the day in which they occurred. The company then reviewed resource costs and benefits reported by Plexos specific to the case in question to determine which types of resources would be most economic to cover the identified need.
Appx B p. 2 climate-as a topic of a public-input meeting to share and discuss approaches to modeling climate risk in the IRP including: proposed changes to how weather and extreme events are considered; proposed changes for the consideration of climate-related risks on supply side
and a discussion on how the Company proposes to include climate change impacts as part of the status quo. We adopt this recommendation and note that we appreciate PacifiCorp's thorough
at several public meetings, including: May 12, 2022 September 1-2, 2022 October 13, 2022 A primary function of these discussions was to discuss the incorporation of climate change as a base
change” study (W-11 Climate Change Counterfactual) is provided in the 2023 IRP.
Appx B p. 2 DSM Updates from a twice-annual report to an annual report.
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43
B p. 1 should provide a metric calin its capacity expansion model
estimate of the relative value of each coal unit to the system.
resource which is available for selection. Each resource’s annual value is calculated, as well as an aggregate value over the period of the study.
B p. 1 provide graphs of the average fixed and variable costs of operating each coal unit over the planning timeframe. This should include fuel cost and run rate capital, but exclude depreciation expense.
materials on the data disc.
B p. 1 development process, PacifiCorp should fully assess the potential for gas conversion; use of hydrogen, biofuel, or other lower-carbon fuels; or alternate coal stockpile or supply methods for Jim Bridger 3 and 4. A report should be included with the 2023 IRP.
fuels at the 2023 IRP June 9-10 public input meeting. “LC 82 (PAC 2023 IRP) – Special Public Meeting – Waivers for extension to file the CEP and Long-Fuel Plan.”
B p. 1 should report on the costs and emissions (CO2 and NOX) of green hydrogen combustion at the converted Bridger unit.
hydrogen, as well as the ability for existing infrastructure to accommodate the chemical properties of this fuel type. The Company’s existing generation equipment is not well suited to green hydrogen combustion because exposure to high-temperature hydrogen results in degradation of many critical alloy components, particularly within steam turbines. Conversion of combustion turbines to hydrogen fueling is more promising, because the hot garisk, but is not yet commercially available for the large turbines in PacifiCorp’s fleet. Conversion of combustion turbines could potentially include combined cycle combustion turbines as steam turbine is not directly exposed to hydrogen
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B p. 1 thoroughly investigate the potential to install a new turbine designed to run on 100 percent green hydrogen at the sites of one or more retiring coal plants.
hydrogen, as well as the ability for existing infrastructure to accommodate the chemical properties of this fuel type. the 2023 IRP allows for non-current coal plant sites and in other locations. These peaking resources were assumed to be fueled using 100 percent green hydrogen, supplied via pipeline due the high cost of onsite storage, but a wide variety of non-emitting currently under development.
B p. 1 costs should be modeled accurately as variable with generation, and not approximated
have been in the 2021 IRP.
IRP.
B p. 2 RFP processes, potential RFP bidders should be given access to a 12x24 Loss of Load Probability matrix for one out of every five years in the IRP planning timeframe.
advance of bid submissions in the 2022 All-Source RFP, PacifiCorp prepared the requested information and provided it to stakeholders in its January 25, 2022 filing in docket UM 2011. Following the completion of the 2023 IRP, PacifiCorp will develop comparable information for use in future RFP processes.

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Reference Recommendation How the Guideline is Addressed in the 2023 IRP
Utah
DOCKET NO. 90-2035-01
p. 33-37 jurisdiction and by general class and will differentiate energy and
capacity requirements. The Company will include in its
forecasts all on-those off-system loads which
they have a contractual obligation to fulfill. Non-firm
off-system sales are uncertain and should not be explicitly incorporated into the load
to meet. However, the Plan must have some analysis of the off-
impacts such markets will have
jurisdiction and by customer class. Further, this forecast includes off-system wholesale customers
for which the Company has a contractual obligation to fulfill. To plan for non-firm off-system customer
impacts returning to PacifiCorp’s system, 1-3-year option direct access customers in Oregon are
incorporated into the forecast assuming they will return once their opt-out period expires.
p. 33-37 economic and 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 efficiency of
inform a least-cost, least-risk preferred portfolio outcome. Changes to consumer behavior are also
outlined under the suite of existing demand-side management, energy efficiency and load forecast projections at the disposal of the Company.
p. 33-37 market opportunities (both demand-side and supply-side), on a consistent and comparable basis.
potential resource options within its supply-side table, and has included reasonable cost all resource types. Where costs and operating characteristics are similar, as with different lithium-ion chemistries, the IRP does not attempt to differentiate – no particular technology is correct,
and differences in performance are expected to be well within the normal range of offers from bidders.Even non-emitting peaking and nuclear resources are ultimately proxies for their particular combinations of costs, operating characteristicsrisks. Many types of risks are expected to evolve
over the next few planning cycles both risks associated with these new technologies, and those associated with emitting technologies.
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46

p. 33-37 feasible and cost-effective
of electricity, including load management and conservation.
cost-effective energy efficiency, conservation, and load management through the Conservation Potential Assessment to compete with other resources in the IRP modeling.
p. 33-37 feasible generating technologies including: renewable resources, cogeneration, power purchases from other sources, and the construction of thermal resources.
feasible generating technologies including: renewable resources, cogeneration, and the construction of thermal resource. The IRP does not represent ownership structures for proxy resources. Any resource could end up being a Build Transfer Agreement (BTA), Power Purchase Agreement (PPA), self-build, or other contract structure.
p. 33-37 include: life expectancy of the resources, the recognition of whether the resource is replacing/adding capacity or energy, dispatchability, lead-requirements, flexibility, efficiency of the resource and opportunities for customer participation.
the resources, the recognition of whether the resource is replacing/adding capacity or energy, dispatchability, lead-time requirements, flexibility, and efficiency of the resource and opportunities for customer participation.
p. 33-37 competitive bidding for demand-side and supply-side resource acquisitions.
the all-source RFP and inputs for assessment was developed so that potential demand side bids could compete with supply side resources. Additionally, demand side resources are evaluated as part of the IRP modeling to evaluate overall competitiveness with other resources.
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47
p. 33-37 through 2042.
p. 33-37 the specific resource decisions intended to implement the integrated resource plan in a manner consistent with the Company's strategic business plan.
(Action Plan).
p. 33-37 specific resource 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
specific actions contained in the
(Action Plan).
p. 33-37 resource options in a manner which rationalizes the choice of resources under a variety of economic circumstances.
load forecasts and price-policy scenarios under which resources compete on an optimized basis for the selection of resource options, retirements, unit
and sales, and other elements. See Volume I, Chapters 7, 8 and 9.
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48

p. 33-37 acquisition paths for different economic circumstances with a decision mechanism to select
the future unfolds.
Volume I, Chapter 10 (Action Plan).
p. 33-37 effectiveness of the resource options from a variety of perspectives and society as a whole.
adjustment metric based on stochastic modeling results, provides a set of competitive variant portfolios, and includes studies assuming a social cost of greenhouse gas cost-adder as a price-policy scenario.
DOCKET NO. 90-2035-01 p. 33-37 associated with various resource options and how the action plan addresses these risks in the context of both the and the 20-year Integrated Resource Plan.
adjustment metric based on stochastic modeling results, and includes a Business Plan sensitivity. The 2023 IRP will be used to inform the Business Plan.
p. 33-37 competitive, reliability, and operational risks associated with
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.
which is reflective of the costs, operational characteristics, technology type, location, interconnection availability and other factors. In addition, the RFP non-price scoring process evaluates, in coordination with several independent evaluators representing three states, the project and reliability risks and scores these The assumptions in the Business Plan and 20-year Integrated Resource Plan are ultimately modified and realized through actual generating projects that are either owned or under contract and represent ratepayer risk, not shareholder risk, except to the extent that the commitments or actions of the Company are deemed imprudent in a future ratemaking proceeding. During RFP procurements,
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49
submitted to regulatory staff upon request or by order or statute. These contracts include performance guarantees to balance the risk between the project owner and the Company on behalf of ratepayers.
p. 33-37 so that the Company can take advantage of opportunities and can prevent the premature foreclosure of options.
against risk and the expense of the development of its supply side resources. The 2023 IRP included discussion of supply side resource, beginning earlier in the public input process than in previous IRPs, and revisited several times. Particular options were considered in
offshore wind. The 2023 IRP also included natural gas resource options, which had been excluded in the 2021 IRP.
p. 33-37 example, between such conditions of service as reliability and the acquisition of lowest cost resources.
between reliability and resource cost, as well as operational costs incurred during dispatch as part of the core functionality of optimization modeling. This is the purpose of the optimization. Additional analysis is provided in narrative form where salient trade-offs are indicated in portfolio outcomes. See Volume I, Chapter 9 (Modeling and Portfolio Selection Results).
p. 33-37 precise 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 externalities.
almost unfathomable potential range of outcomes, many of which may be contradictory with other rules or policy goals, as in restrictions on non-emitting resources. What is certain, is that compliance may involve costs dramatically in excess of even the social cost of greenhouse gases price-policy scenario. As an example, coal ash handling and water treatment is only partly related to ongoing operations, but the costs could offset years of possible operational benefits depending on the circumstances. Environmental and safety regulation is not limited to fossil fuel resources, a few very basic examples include: - Very few battery chemistries have significant history in utility-scale operations, and some
PACIFICORP – 2023 IRP APPENDIX B – IRP REGULATORY COMPLIANCE
50

bats. - Cadmium telluride solar panels include two toxic chemicals, which while significantly less harmful in compound form, do not have well documented long-term effects. The above is not intended to be comprehensive - all technologies have trade-offs and risks though some technologies have more unknown unknowns than others. The largest externality of which the Company is currently aware is the impact of greenhouse gases on the climate. A price-policy scenario with an estimate of the social cost of greenhouse gases is used to quantify that particular externality, and analysis including those costs is presented for the preferred portfolio and selected
p. 33-37 other interested parties will have the opportunity to make formal comment to the Commission on the adequacy of the Plan. The Commission will revfor 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 to the Commission's acknowledgement 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 acknowledgement of the Integrated Resource Plan might be appropriate but are not
an acceptable Plan will not guarantee favorable ratemaking treatment of future resource
process.
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51
5-8 Guidelines 4(b) and 4(i) by not constraining its model to
gas resources
which had been excluded in the 2021 IRP.
9-18 business days in advance of public meetings
to stakeholders via email within the parameters of this requirement. See Volume II, Appendix C (Public Input).
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52

2035-01 p. 33-37 used in rate cases to evaluate the performance of the utility and to review avoided cost calculations.

Reference IRP Requirement or Recommendation How the Guideline is Addressed in the 2023 IRP
Washington
State Rule/Statute Requirement greenhouse gases (SCGHG) as a cost adder, as required by RCW
illustrating step-by-step how the SCGHG cost adder is applied throughout its modeling logic. The SCGHG impact on the Company’s modeling and portfolio analyses should be addressed in numerous variables, including PacifiCorp’s imports and contracts and forward
provided a narrative framework outlining carbon price policy scenario assumptions and nominal electric and natural gas price inputs, which were discussed at the February 23, 2023 Public Input meeting.
Requirement resource evaluations into a long-IRP solution describing the mix of resources that meet current and
variety of constraints pursuant to statute and per Commission rule. WAC 480-100-620(11)
a comparable basis following the requirements in statute and appropriate to this filing’s status as a Two-Year Progress Report. See Chapter 8 and Appendix O.
Requirement pumped storage for integrating renewable resources. The assessment may consider ancillary services at the appropriate granularity required to model such storage resources. WAC
incorporates multiple storage options including lithium-ion, flow and iron-air batteries, and pumped hydro storage. Modeling was conducted at appropriate granularity in the Plexos LT, MT and ST models. See Volume I, Chapters 7 and 8.
Requirement meets the requirements of WAC 480-100-scenario must be a future climate
incorporate the best science available to analyze impacts including, but not limited to, changes in snowpack, streamflow, rainfall, heating and
impacts on the load forecast, energy efficiency potential, and the hydro generation forecast. The load forecast for the 2023 IRP is based on a Bureau of Reclamation median projection of climate impacts through time on heating and cooling degree days, resulting in increasing divergence from the 20-year normal weather further in the IRP planning horizon. The hydro forecast similarly relies on projected
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53
horizon. A scenario using the 20-year normal weatherforecast for load and hydro was prepared for comparison purposes.
Requirement adequacy requirement (i.e., loss of load probability) and complete the assessment, as required by WAC 480-100-620(8)
Report and is not explicitly addressed in terms of avoided cost in this filing. However, the Progress Report includes expanded reporting of reliability assessment including identifying deficiencies and the resolution of deficiencies based on model outcomes. The Plexos modeling process and the ENS metric
Requirement market forecasts used in the utility's schedule of estimated avoided costs required in WAC 480-106-040, including but not limited to: -Cost Assumptions -Production Estimates -Peak capacity contribution estimates
Report and is not explicitly addressed in terms of avoided cost in this filing. However, resource assumptions, capacity factors and price forecasts are included in workpapers. PacifiCorp would note that its 2023 IRP uses forward market prices from September 2022, which is the same vintage as PacifiCorp’s November 1, 2022 avoided cost filing
Requirement resources and potential changes to existing resources for achieving the
in WAC 480-100-610 at the lowest reasonable cost, including a narrative of the decisions it has made. WAC
all resource options in its optimized evaluation, and provides narratives of comparative analysis of outcomes in Volume I, Chapter 9, and details regarding resource attributes in Volume I, Chapter 7.
IRP must include a range of forecasts of projected customer demand that reflect the effect of economic forces on the consumption of electricity and address changes in the number, type, and efficiency of end uses of electricity.
including climate change impacts 2.) Optimistic and Pessimistic assumptions in the low and high growth models and how these alternative forecasts differ from the base forecast 3.) Electrification adjustments made
scenarios. Also, to account for changes in the number, type and efficiency of end-uses, the Company updates its statistically adjusted end-use model used in the load forecast. See Volume II, Appendix A (Load Forecast) for details regarding the alternative load forecast scenarios. Specifically, the Company’s base forecast includes expected climate change impacts on loads, while the 20-year normal load forecast scenario provides the load forecast without explicitly accounting for climate change temperatures. Further, the Company does produce both optimistic and pessimistic load forecast scenarios. Please refer to Appendix A (Load Forecast) for details regarding transportation and building electrification adjustments made to the load forecast.
Requirement with the requirement in RCW 19.280.030(1)(m) regarding electric and zero-emission vehicles. RCW 19.280.030(1)(m) An analysis
vehicles using the methods to determine utility impacts described in the Company’s Washington Transportation Electrification Plan. PacifiCorp develops multiple electric vehicle adoption futures
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(I) Modeled load forecast scenarios that consider the anticipated levels of zero emissions vehicle use in a utility's service area, including anticipated levels of zero emissions
provided in RCW 47.01.520, if feasible; (ii) Analysis, research, findings, recommendations, actions, and any other relevant information found in the electrification of transportation plans submitted under RCW 35.92.450, 54.16.430, and 80.28.365; and (iii) Assumed use case forecasts and the associated energy impacts. Electric utilities may, but are not required to, use the forecasts generated by the mapping and forecasting tool created in RCW 47.01.520. This subsection (1)(m)(iii) applies only to plans due to be filed
emission vehicle forecast in September of 2022 account for impacts from the inflation reduction act and recently adopted ZEV standards.
Requirement non-to those applied during conservation potential assessment (CPA) development. WAC 480-100-620(11)(g)
a DNV NEI study in 2021 which developed a comprehensive assessment of NEIs. In response to stakeholder comments about NEI valuation, PacifiCorp revisited assumptions and presented results at the April 28, 2022, DSM advisory group meeting. Upon finalization of results, PacifiCorp mapped measure specific NEI’s to measures in the conservation potential assessment. This represents a broader application of NEIs compared to the prior study which used a proxy value adder to represent NEI valuation. Additionally, for demand response, a literature review was conducted to determine if there were any program specific NEIs. Since no quantitative values were found in the literature review, PacifiCorp chose to include a 10% adder to approximate NEI impacts for demand response. In the prior study, no NEI’s were included for demand
Requirement whether nonenergy costs and benefits accrue to the utility, customers, participants, vulnerable populations, highly impacted communities, and/or the general public. WAC 480-100-
Energy Impact Mapping”, as part of the CPA supplemental materials posted on the website, maps the accrual of NEIs to various groups consistent with WAC 480-100-620(13).
Requirement -Publ2023 IRP development (rather than providing a download of stakeholder
requirement by publishing all stakeholder comments received and associated responses in a centralized location externally. The narrative stakeholder form received is also outlined in greater
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55
-PacifiCorp corresponding responses to public comment -Whether and how the final plan addresses and incorporates comments
Requirement potential assessments (WAC 480-100620(3)(b)) Sub-section (iii) (energy assistance potential assessment)--The IRP must include distributed energy programs
RCW 19.405.120, which pertains to
meeting energy assistance need. Sub-section (iv) (other DER potential assessments) – The IRP must assess other DERs that may be installed by the utility or the utility's customers including, but not limited to, energy storage, electric vehicles, and photovoltaics. Any such assessment must include the effect of DERs on
potential assessment(s) must go beyond the utility’s legacy approach showing DERs as simply a load forecast decrement
through a variety of methods. PacifiCorp evaluates private generation by considering varying levels of technology costs and electricity rate assumptions,
low private generation load forecast sensitivities. With regard to the energy assistance potential assessment, PacifiCorp evaluates energy efficiency potential by income level so as to inform how energy
The 2023 IRP also assesses other DERs such as energy storage, which is considered within the Company’s private generation study and the CPA as a demand response resource for acquisition is subsequently incorporated into PacifiCorp’s load forecast and IRP modeling. Further, utility scale battery storage is considered as a resource option within the context of portfolio analysis. The
the load forecast along with the control of electric vehicle load as a demand response resource in the IRP model.
Requirement interest meetings (PIMs) informing
cycle, circulate completed
presentation materials at least three business days prior to each meeting.
stakeholders via email within the parameters of this
requirement.
Commission in native format with
made by
accompanying data disk(s). Dockets
UE-191023 and UE-190698, General
adhere to this requirement within the limits of
listing of file names with a description of the file’s
content or purpose. This information is provided on the data disk.
the Company’s preferred portfolio. Dockets UE-191023 and UE-190698,
General Order R-601 at 60-61, ¶ 173 and 178
workpapers for each portfolio including the preferred portfolio.
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demonstrate progress towards identifying, researching, and properly valuing NEIs. Docket UE-210830, Order 01, Attachment A, condition 11a
advisory group on October 12, 2021, February 28, 2022 group on June 16, 2022. These discussions sought feedback on NEI valuation, research and application. The 2023 CPA included measure specific NEIs for energy efficiency and proxies for demand response that were more substantive and comprehensive
utility files its IRP, beginning January 1, 2023, the utility must file a two-year progress report. (a) In this report, the utility must update its: (i) Load forecast; (ii) Demand-side resource assessment, including a new conservation potential assessment; (iii) Resource costs; and (iv) The portfolio analysis and preferred portfolio. (b) The progress report must include other updates that are necessary due to changing state or federal requirements, or significant changes to economic or market forces. (c) The progress report must also update for any elements found in the utility's current clean energy implementation plan, as described in WAC 480-100-640.
updated Demand-side management potential assessment, updated resource cost assumptions and portfolio analysis including the preferred portfolio. Please refer to Appendix O (Washington 2021 IRP Two-year Progress Report Additional Elements), for additioClean Energy Implementation Plan.

Reference IRP Requirement or Recommendation How the Guideline is Addressed in the 2023 IRP
Wyoming
Order, Docket No. 90000-
144-XI-19 (Record No. 15280) on the 2017 IRP Updated Preferred Portfolio, incorporating updated assumptions, such as load and
market prices and any known
using environmental investments or costs only required by current law. For
Additional information on the specified reference case can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
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emissions absent an existing legal requirement.
144-XI-19 (Record No. 15280) analysis of the impact of alternative price-policy scenarios on the resource plan.
plan is summarized in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection).
144-XI-19 (Record No. 15280) on top performing portfolio cases and the reference case. found within Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and
Order, Docket No. 90000-144-XI-19 (Record No. 15280)
Demonstrate rate impacts over the planning period between preferred portfolio and the reference case.
The 2023 IRP includes reference case P02-JB3-4 EOL, which continues Wyoming coal through end-of-life until necessity of gas conversion or other treatment driven by major by environmental
144-XI-19 (Record No. 15280) methodologies to integrate different reliability analyses including regional analysis of resource adequacy; analysis of power flow issues caused by retiring coal units; study of potential weather-related outages on intermittent generation; and an analysis of
IRP – Volume I, Chapter 5 (Reliability and Resiliency) – which includes regional analyses of
caused by baseload resource retirements and how PacifiCorp Transmission is planning for those retirements, an assessment of weather-related outages, and a discussion of wildfire risk and mitigation.
144-XI-19 (Record No. 15280) operational experience, if any, with battery acquisition and
of capabilities learned from
and operational experience with battery acquisition and operations as part of Volume I, Chapter 7 (Resource Options).
144-XI-19 (Record No. 15280) will maximize the use of
dispatchable and reliable low-carbon electricity pursuant to
and Sequestration analysis within the portfolio modeling process. Volume I, Chapter 8 (Modeling
and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results).
144-XI-19 (Record No. 15280) and to the extent there are outstanding material disagreements regarding cost allocation at the time of filing, quantify those risks and potential impact to Wyoming
status of the MSP within Volume I, Chapter 3 (Planning Environment). As there are no agreed-changes or outstanding material disagreements, PacifiCorp did not quantify potential impacts. To the extent that there are changes and/or material
include the required quantified risk.
144-XI-19 (Record No. 15280) generation types including nuclear and natural gas. included in the supply-side table as part of the 2023 IRP. Advanced nuclear and natural gas resources have both been included in the supply-side table and
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term storage options.
144-XI-19 (Record No. 15280) impacts and regulatory framework for renewable generation.
Planning Environment discussion in Volume I, Chapter 3 (Planning Environment).
144-XI-19 (Record No. 15280) that each of these requirements are addressed in the 2023 IRP addressed each within the 2023 IRP.

Reference IRP Requirement or Recommendation How the Guideline is Addressed in the 2023 IRP
California
D.18-02-018

D.22-02-004
Public Utilities Code §§ 399.13(a)(7), 454.5, 454.52
Communities
Provide supplemental information about disadvantaged communities, including “a demonstration of how disadvantaged communities were considered.” (D.18-02-018, p. 135.)
“PacifiCorp is required to supplement its multi-state IRP with … specific information on … a separate demonstration that satisfies the requirements for disadvantaged communities.” (D.22-02-004, p. 22.)
“At a minimum, all LSEs shall
provide the following information in their IRPs:
i. A description of which disadvantaged communities, if any,
it serves (LSEs will be expected to make the determination of what is
considered “disadvantaged” every two years);
ii. What current and planned LSE activities/programs, if any, impact
disadvantaged communities; and iii. A qualitative description of the
demographics of the customers it serves and how it is currently
addressing or plans to comply with the requirement to minimize air
pollutants.” (D.18-02-018, p. 68.)
PacifiCorp serves fewer than 50,000 customers in
mostly rural northern California, with a significant
number of customers on energy assistance programs.
PacifiCorp’s California customers are geographically-
dispersed, with approximately four customers per square
mile. 3.
PacifiCorp is committed to affordability to protect
disadvantaged communities. In PacifiCorp’s most
current general rate case, which is currently pending at
the California Public Utilities Commission, the company
has requested recovery of costs associated with the
addition of investments in renewable generation
resources. Those resources reduce overall emissions
and provide zero-fuel cost energy and production tax
credits that benefit our customers. PacifiCorp also
proposed an increase to its California Alternative Rates
for Energy discount from 20 percent to 25 percent, new
time varying rate options, and paperless bill credit,
among other changes, to support customers during
increased costs for wholesale energy and wildfire
mitigation.

In 2023, PacifiCorp plans to transition its Home Energy
Savings residential energy efficiency program from a
resource acquisition program to an equity program
targeting Hard-to-Reach and Tribal csutomers. In
addition, PacifiCorp filed an advice filing requesting approval to offer Home Energy Reports as an equity
program targeting only Hard-to-Reach and Tribal

3 SB 535 Disadvantaged Communities | OEHHA (ca.gov)
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If we wish to provide additional information, we can address how
PacifiCorp is:
• strengthening “the diversity, sustainability, and resilience of the bulk
distribution systems, and local communities.” (D.18-02-018, p. 66; Pub. Util. Code § 454.52.)
• minimizing “localized air
greenhouse gas emissions, with early priority on disadvantaged communities.” (D.18-02-018, p. 66; Pub. Util. Code § 454.52.)
• giving “preference to renewable energy projects that provide environmental and economic benefits to communities afflicted with poverty or high unemployment, or that suffer from high emission levels of toxic air contaminants, criteria pollutants, and greenhouse gases.” (D.18-02-018, p. 67; Pub. Util. Code § 399.13(a)(7).) In soliciting bids for new gas-fired generating units, PacifiCorp should “actively seek bids for resources that are not gas-fired generating units located in communities that suffer from cumulative pollution burdens, including, but no [sic] limited to, high emission levels of toxic air contaminants, criteria air pollutants, and greenhouse gases.” (D.18-02-018, p. 67; Pub. Util. Code § 454.5(b)(9)(D).)
PacifiCorp IRP identifies increased investment in non-
emitting resources to service all of its customers.
Further, PacifiCorp does not own or operate any thermal
generation in California that would negatively impact
communities in the California service area.
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D.22-02-004
ALJ Ruling Finalizing Load Forecasts and Greenhouse Gas Emissions Benchmarks for 2022 Integrated Resource Plan Filings
“PacifiCorp should consult with
Commission staff and describe an alternative [to the CNS/CSP
Calculator] methodology that addresses its share of the 2030 GHG
emissions reduction responsibility.” (D.19-04-040, p. 74.)
“PacifiCorp is required to supplement its multi-state IRP with … specific information on … another (non-CSP calculator) method to fulfill requirements that would otherwise have required the CSP tool and justification for the choice.” (D.22-02-004, p. 22.)
PacifiCorp’s GHG benchmarks are available here: https://www.cpuc.ca.gov/-/media/cpuc-website/divisions/energy-division/documents/integrated-resource-plan-and-long-term-procurement-plan-irp-ltpp/2022-irp-cycle-events-and-materials/2022-final-ghg-emission-benchmarks-for-
its alternative methodology to address GHG benchmarks. PacifiCorp’s IRP supplement will include the results of the emissions forecast in California relative to GHG Benchmark.

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Table B.3 – Oregon Public Utility Commission IRP Standard and Guidelines
No. Requirement How the Guideline is Addressed in the 2023 IRP
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 7 (Resource Options), and Chapter 8 (Modeling and Portfolio Evaluation) 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, Plexos, and selected by the model based on load requirements, relative economics, resource size, availability dates,
1.a.2 All resources must be evaluated on a consistent and comparable basis:
Utilities should compare different resource fuel types, technologies, lead times, in-service dates, durations and locations in portfolio risk modeling.
All portfolios developed with Plexos were 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 8 (Modeling and Portfolio Evaluation), Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix I (Capacity Expansion Results) and Appendix J (Stochastic Simulation
1.a.3 All resources must be evaluated on a consistent and comparable basis:
Consistent assumptions and methods should be used for
evaluation of all resources.
PacifiCorp fully complies with this requirement. The 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 documented in Volume I, Chapter 6 (Load and Resource Balance), Chapter 7 (Resource Options), and Chapter 8 (Modeling and Portfolio Evaluation) as well as
a consistent and comparable basis: The after-tax marginal weighted-
average cost of capital (WACC) should be used to discount all
6.77 percent to discount all cost streams.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
1.b.1 Risk and uncertainty must be considered: 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 emissions.
is treated as a stochastic variable in PacifiCorp’s production cost simulation apart from CO2 emission compliance costs, which are treated as a scenario risk and evaluated as part of a CO2 price assumption and a no CO2, a high CO2, and a social cost of carbon price-policy scenario for specific studies. See Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Volume I, Chapter 9 (Modeling and Portfolio
considered: Utilities should identify in their plans any additional sources of risk and uncertainty.
Chapter 10 (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 (Planning Environment), Chapter 4 (Transmission), Chapter 8 (Modeling and Portfolio Evaluation), and Chapter 9
a 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 9 (Modeling and Portfolio Selection Results), Chapter 10 (Action Plan), and Volume II, Appendix I (Capacity Expansion Results) and Appendix H (Stochastic Parameters) for the company’s portfolio cost/risk analysis and determination of the preferred
choices should be at least 20 years and account for end effects. Utilities should
consider all costs with a reasonable likelihood of being included in rates over
the long term, which extends beyond the planning horizon and the life of the
for portfolio modeling, and a real levelized revenue requirement methodology for treatment of end effects.
revenue 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) provides a description of the PVRR methodology.
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No. Requirement How the Guideline is Addressed in the 2021 IRP
1.c.3.1 To address risk, the plan should include, at a minimum: 1. Two measures of PVRR risk: one that measures the variability of costs and one that measures the severity of bad
production costs as the measure of cost variability. For the severity of bad outcomes, the company calculates several measures, including stochastic upper-tail mean PVRR and the 95th percentile stochastic production
minimum: 2. Discussion of the proposed use and impact on costs and risks of physical and
Chapter 10 (Action Plan).
its 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 (Modeling and Portfolio Evaluation) 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 (Planning Environment). Volume I, Chapter 9 (Modeling and Portfolio Selection Results) provides the results. Volume I, Chapter 10 (Action Plan) presents an acquisition path analysis that describes
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 Oregon
Volume II, Appendix C (Public Input) provides an overview of the public input process, all public-input meetings held for the 2023 IRP, and summarizes public input received throughout the 2023 IRP cycle. PacifiCorp also made use of a Stakeholder Feedback Form for stakeholders to provide comments and offer suggestions. Stakeholder Feedback Forms along with responses and the public-input meeting presentations are available on PacifiCorp’s webpage at: w ww.pacificorp.com/energy/integrated-resource- p lan.html
2.b While confidential information must be 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 Oregon PUC.
2023 IRP Volumes I and II provide non-confidential information 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 and in response to Stakeholder Feedback Forms. Data discs will be available with public data. Additionally, data discs with confidential data will be provided to appropriate parties through use of a
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public review and comment prior to filing a final plan with the Oregon PUC. review throughout the process prior to each of the public input meetings and solicited/and received feedback at various times when developing the 2023 IRP. The materials shared with stakeholders at these meetings, outlined in Volume II, Appendix C (Public Input), is consistent with materials presented in Volumes I and II of the 2023 IRP report.
PacifiCorp requested and responded to comments from stakeholders when establishing modeling assumptions and throughout its portfolio-development process and
Guideline 3: Plan Filing, Review, and Updates
of 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
3.b The utility must present the results of its filed plan to the Oregon PUC at a public meeting prior to the deadline for written
This activity will be conducted following the filing of this IRP.
3.c Commission staff and parties should complete their comments and recommendations within six months of IRP
This activity will be conducted following the filing of this IRP.
3.d The Commission will consider comments and 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 IRP before issuing an acknowledgment
This activity will be conducted following the filing of this IRP.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
3.e The Commission may provide direction to a utility regarding any additional analyses or actions that the utility should undertake in its next IRP.
3.f (a) Each energy utility must submit an annual 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 Oregon PUC, unless the utility is within six months of filing its next IRP. The utility must summarize the update at an Oregon PUC public meeting. The utility may request acknowledgment of changes in proposed actions identified in an
Not applicable to this filing; this activity will be conducted following the filing of this IRP.
of changes in proposed actions, the annual update is an informational filing that:
• Describes what actions the utility has taken to implement the plan;
• Provides an assessment of what has changed 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 acknowledged action
conducted following the filing of this IRP.
Guideline 4. Plan Components:
No. Requirement How the Guideline is Addressed in the 2023 IRP
4.a An explanation of how the utility met each of the substantive and procedural requirements. guideline.
4.b Analysis of high and low load growth scenarios in addition to stochastic load risk analysis with an explanation of major assumptions.
PacifiCorp developed low, high, and extreme peak temperature (one-in-twenty probability) load growth forecasts for scenario analysis using the Plexos model. Stochastic variability of loads was also captured in the risk analysis. See Volume I, Chapters 6 (Load and Resource Balance) and Chapter 8 (Modeling and Portfolio Evaluation), and Volume II, Appendix A
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No. Requirement How the Guideline is Addressed in the 2023 IRP
4.c For electric utilities, a determination of the levels of peaking capacity and energy capability expected for each year of the plan, given existing resources; identification of capacity and energy needed to bridge the gap between expected loads and resources; modeling of all existing transmission rights, as well as future transmission additions associated with the resource portfolios
details 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 8 (Modeling and Portfolio Evaluation).
supply-side and demand side resource options, considering 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 Resources) referencing
take to provide reliable service, including cost-risk tradeoffs. for all portfolios evaluated, as supported by an updated Stochastic Loss of Load Study in Volume II, Appendix J (Stochastic Simulation Results), 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 8 (Modeling and
the future (e.g., fuel prices and environmental compliance costs) and alternative scenarios considered.
Evaluation) describes the key assumptions and alternative scenarios used in this IRP. Volume II, Appendix I (Capacity Expansion Results) includes summaries of assumptions used for each case
4.h Construction of a representative set of resource 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 system.
This IRP documents the development and results of portfolios designed to determine resource selection under a variety of input assumptions in Volume I, Chapters 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results).
4.i
identified risks and uncertainties.
Volume I, Chapter 9 (Modeling and Portfolio Selection Results) incorporates the stochastic portfolio modeling results as described in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), and describes portfolio attributes that explain relative differences in
4.j Results of testing and rank ordering of the portfolios by cost and risk metric, and interpretation of those results.
Volume I, Chapter 9 (Modeling and Portfolio Selection Results) provides tables and charts with performance measure results, including rank ordering.
each portfolio evaluated.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
4.l Selection of a portfolio that represents the best combination of cost and risk for the
utility and its customers.
See 1.c above.
inconsistencies of the selected portfolio with any state and federal energy policies that may affect a utility’s plan and any
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
IRP action plan.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
5 Portfolio analysis should include costs to the 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 reliability.
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. In addition to endogenous resource and transmission selects, the 2023 IRP modeled seven variants’ cases to evaluate Energy Gateway and its components, B2H, and
Cluster 1 and 2 transmission. See Volume I, Chapter 8 (Modeling and Portfolio Evaluation), and specifically
Guideline 6: Conservation
conservation potential study is conducted periodically for its entire service territory. on the company’s webpage, and the most recent results from the conservation potential assessment
6.b To the extent that a utility controls the level of 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.
PacifiCorp’s energy efficiency supply curves 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 7 (Resource Options), the results in Volume I, Chapter 9 (Modeling and Portfolio Selection Results), the targeted amounts in Volume I, Chapter 10 (Action Plan) and the implementation steps outlined in Volume II, Appendix D (DSM
6.c To the extent that an outside party administers 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.
See the response for 6.b above.
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 (for natural gas
(DSM) on a consistent basis with other resources.
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Guideline 8: Environmental Costs
No. Requirement How the Guideline is Addressed in the 2023 IRP
8.a Base case and other compliance scenarios: The 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 an allowance for 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
See Volume I, Chapter 8 (Modeling and Portfolio Evaluation).

In the 2023 IRP, PacifiCorp’s base assumption includes a proxy price on CO2 starting in 2025 within the medium gas/medium (“MM”) CO2 price-policy scenario for evaluation of all portfolios. In addition PacifiCorp modeled a high gas/high CO2 (“HH”) and a Social Cost of Greenhouse Gas price-policy scenario (“SC”) for the preferred portfolio and relevant variants.
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 preferred portfolio selection.
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 8 (Modeling and Portfolio Evaluation) 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.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
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
Evaluation) for a description of initial portfolio development definitions. Comparative analysis of these case results is included in Volume I, Chapter 9 (Modeling and Portfolio Selection Results).
8.d Oregon compliance portfolio: If none of the 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
Several portfolios yield system emissions aligned with state goals for reducing greenhouse gas emissions. These cases are summarized in Volume I, Chapter 9 (Modeling and Portfolio Selection Results).

PacifiCorp’s Clean Energy Plan will filed by June 1,
2023, incremental to the statewide 2023 IRP preferred portfolio outcomes.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
9 An electric utility’s load-resource
balance should exclude customer loads that are effectively committed to
service by an alternative electricity
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
10 Multi-state utilities should plan their generation 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.
The 2023 IRP conforms to the multi-state planning approach as stated in Volume I, Chapter 2
(Introduction) 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
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 stated
(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.
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
Guideline 13: Resource Acquisition
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No. Requirement How the Guideline is Addressed in the 2023 IRP
13.a An electric utility should, in its IRP: 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.
procurement 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 10 (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 2023
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 generation over the
Appendix F (Flexible Reserve Study).
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.
Appendix F (Flexible Reserve Study).
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 EVs, on a
Appendix F (Flexible Reserve Study).
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Table B.4– Utah Public Service Commission IRP Standard and Guidelines
No. Requirement How the Guideline is Addressed in the 2023 IRP
1 The Commission has the legal authority to promulgate Standards and Guidelines for of Utah responsibility.
method for developing and implementing the 2023 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
I, Chapter 2 (Introduction). A description of public-input meetings is provided in Volume II, Appendix C (Public Input). Public-input meeting materials can also be found on PacifiCorp’s website at: www.pacificorp.com/energy/integrated- resource-plan/public-input-process.html
attendant costs must be included in the integrated resource planning analysis. with externality cost adders to model environmental externality costs. See Volume I, Chapter 8 (Modeling and Portfolio Evaluation) for a description of the methodology employed, including how CO2 cost uncertainty is factored into the determination of relative portfolio performance through a base case planning assumption and other
6 The integrated resource plan must evaluate supply-side and demand-side resources on a consistent and comparable basis.
Supply, transmission, and demand-side resources were evaluated on a comparable basis using Plexos optimization models. Also see the response to
7 Avoided cost should be determined in a manner
Plan.
Consistent with Utah rules, PacifiCorp determination of avoided costs in Utah will be handled in a manner consistent with the IRP, with the caveat that the costs may be updated if better
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.
9 The company's Strategic Business Plan must be directly related to its Integrated Resource Plan. Volume I, Chapter 10 (Action Plan) describes the linkage between the 2023 IRP preferred portfolio
and December 2022 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,
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No. Requirement How the Guideline is Addressed in the 2023 IRP
1 Definition: Integrated resource planning is a utility planning process which evaluates all known resources on a consistent and comparable basis, 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) outlines the portfolio performance evaluation and preferred portfolio selection process, while Chapter 9 (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-
Plan biennially. 2021, and filed this IRP on March 31, 2023, as an informational filing, meeting the requirement. PacifiCorp requested and was granted a 60 day extension of time to file the final 2023 IRP on May 31,
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
Chapter 2 (Introduction). A record of public meetings and a summary of feedback and public comments is provided in Volume II, Appendix C (Public Input).
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 2021 IRP are provided in Volume I, Chapter 7 (Resource Options) and Volume
4.a.i The forecasts will be made by jurisdiction and by 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 uncertain and should not be explicitly incorporated into the load forecast that the utility 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 associated with different
Load forecasts are differentiated by jurisdiction and differentiate energy and capacity requirements. See Volume I, Chapter 6 (Load and Resource Balance) and Volume II, Appendix A (Load Forecast). Non-firm off-system sales are not incorporated into the load forecast. Off-system sales markets are included in IRP modeling and are used for system 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 efficiency of end-uses will affect future
how demographic and price factors are used in PacifiCorp’s load forecasting methodology.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
4.b An evaluation of all present and future resources, including future market opportunities (both demand-side and supply-side), on a consistent and comparable basis.
comparable basis using the Plexos optimization models for both supply side and demand side alternatives. See explanation in Volume I, Chapter 7 (Modeling and Portfolio Evaluation) and the results in Volume I, Chapter 9 (Modeling and Portfolio Selection Results). Resource options are summarized in Volume I, Chapter 7 (Resource
4.b.i An assessment of all technically feasible and cost-effective improvements in the efficient use of electricity, including load management and conservation.
PacifiCorp included supply curves for Demand Response (dispatchable/schedulable load control) and Energy Efficiency in its capacity expansion model. Details are provided in Volume I, Chapter 7
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. Newly evaluated resources in this IRP include offshore wind and long-term storage options. Volume I, Chapters 7 (Resource Options) and 8 (Modeling and Portfolio Evaluation) contain assumptions and describe the process under which PacifiCorp developed and assessed these
4.b.iii The resource assessments should include: life 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.
PacifiCorp captures and models these resource 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.
for demand-side and supply-side resource acquisitions other procurement methods is provided in Volume I, Chapter 10 (Action Plan).
4.d A 20-year planning horizon. This IRP uses a 20-year study horizon (2023-2042).
4.e An action plan outlining the specific resource 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
The IRP action plan is provided in Volume I, Chapter 10 (Action Plan). A status report of the actions outlined in the previous action plan (2019 IRP Update) is provided in Volume I, Chapter 10 (Action Plan).

In Volume I, Chapter 10 (Action Plan) Table 10.1 identifies actions anticipated in the next two-to-four years.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
4.f A plan of different resource acquisition paths for 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 tax incentives and procurement
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.
total resource cost information in Volume I, Chapter 7 (Resource Options).

The IRP document addresses the impact of social concerns on resource cost-effectiveness in the following ways:
● Relevant portfolios were evaluated using a range of CO2 price-policy scenarios.
● A discussion of environmental policy status and impacts on utility resource planning is provided in Volume I, Chapter 3 (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 9 (Modeling and Portfolio Selection Results). In addition, distinct state filings also address clean energy.
● Volume II, Appendix G (Plant Water
Consumption) reports historical water consumption
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No. Requirement How the Guideline is Addressed in the 2023 IRP
4.h An evaluation of the financial, competitive, reliability, and operational risks associated with various resource options and how the action plan addresses these risks in the context of both the Business Plan and the 20-year Integrated Resource Plan. The company will identify who should bear such risk, the ratepayer, or the stockholder.
I, Chapter 10 (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 Volume I, Chapter 4 (Transmission).

Resource capital cost uncertainty and technological risk is addressed in Volume I, Chapter 7 (Resource Options).

For reliability risks, the stochastic simulation model incorporates stochastic volatility of forced outages for new thermal plants and hydro availability. These risks are factored into the comparative evaluation of
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 discussed
planning process so that the company can take advantage of opportunities and can prevent the premature foreclosure of
is highlighted in Volume I, Chapter 10 (Action Plan).
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 9 (Modeling and Portfolio
4.k A range, rather than attempts at precise quantification, of estimated external costs which may be intangible, 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 number of emissions released and dollar estimates of the costs of such externalities.
PacifiCorp incorporated environmental externality 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 8 (Modeling and Portfolio Evaluation).
4.l A narrative describing how current rate design is consistent with the company's integrated resource planning goals and how changes in rate design might facilitate integrated resource planning objectives.
See Volume I, Chapter 3 (Planning 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 7 (Resource Options).
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public comment, review and acknowledgment. review throughout the process prior to each of the public-input meetings and solicited/and received feedback at various times when developing the 2023 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 2023 IRP report. Public-input meetings materials can be located on PacifiCorp’s website at: www.pacificorp.com/energy/integrated-resource-plan/public-input-process.html

PacifiCorp requested and responded to comments from stakeholders in throughout its 2023 IRP process. The company also considered comments received via Stakeholder Feedback Forms that can be located on PacifiCorp’s website at: www.pacificorp.com/energy/integrated-resource-plan/comments.html A total of 133 Stakeholder Feedback Forms were received and responded to
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
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No. Requirement How the Guideline is Addressed in the 2023 IRP
7 Acknowledgment of an acceptable Plan will not guarantee favorable ratemaking treatment of
cases to evaluate the performance of the utility

Washington IRP requirements and the Washington IRP Two-Year Progress Report
Requirements for the Two-Year Progress Report are significantly reduced compared to the four-year filing of the full IRP. Requirements are focused primarily on fundamental data input updates necessary to update some interim and specific targets and report progress on other elements of the Clean Energy Implementation
Plan. Nonetheless, PacifiCorp has attempted to adhere to all IRP filing requirements where possible in addition to the requirements of the Two-Year Progress Report, as detailed below.
Table B.5 – Washington Utilities and Transportation Commission IRP Standard and Guidelines to Implement CETA Rules (RCW 19.280.030 and WAC 480-100-620 through WAC 480-100-630) per Commission General Order R-601.
No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100-625(1) and (4) four years, with a progress report at least every two years. updates in the off cycles. This exceeds Washington State requirements. New to this IRP cycle is the requirement to file an IRP Two-Year Progress Report.
100-620(1) evaluations, and forecasts comprising the plan should extend over the long-range (e.g., at least ten years; longer if appropriate to the life of the resources considered) planning horizon.
long-term planning horizon. Additional analysis may extend beyond the 20-year horizon but not in the form of optimization modeling runs, as sufficient data is unavailable, resources insufficient and run times, which advance geometrically and not linearly with added years, are impractical. Rather than extrapolate all data inputs to cover longer periods,
100-620(2) projected customer demand that reflect effect of economic forces on electricity consumption.
load, 1-in-20 load, High/low private generation, New Load and No Climate change load scenarios. Other load variants will be considered based on stakeholder feedback and model outcomes.
100-620(2) projected customer demand that address changes in the number, type, and Volume II, Appendix A (Load Forecast). Information can also be found in Volume I,
100-620(3)(a) assessments that are cost-effective and commercially available, including current and new policies and programs to obtain:
conservation potential assessment, which is available on PacifiCorp’s website. Additional information on the load management assessments can be found in Volume II, Appendix D (Demand-Side Management
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100-620(3)(a) efficiency, and load management improvements; energy efficiency and demand response in each case portfolio as a part of core model functionality. Results are reported for all portfolios in Volume I, Chapter 9
109-100(2) the concurrent biennial conservation plan consistent with RCW 19.285.040(1); potential assessment, which is available on PacifiCorp’s website. Volume I, Chapter 6 (Load and Resource Balance) provides additional detail.
combined heat and power as an energy and capacity resource; and component of the Private Generation Study, which is included in Volume II, Appendix L (Private
No. Requirement How the Guideline is Addressed in the 2023 IRP
100-620(3)(b) reasonable cost (LRC). energy efficiency and demand response in each case portfolio as a part of core model functionality. Results are reported for all portfolios in Volume II, Chapter 9
100-620(3)(b) energy programs and mechanisms pertaining to energy assistance and progress toward meeting energy assistance need, including but not limited to the
following: - Energy efficiency and CPA, - Demand response potential,
and demand response potential, and distributed energy programs. Evaluation is detailed in Volume I, Chapter 8 (Modeling and Portfolio), and Chapter 9 (Modeling and Portfolio Selection Results).
100-620(3)(b) energy resources (DER) that may be installed by the utility's customers via a
planning process pursuant to RCW 19.280.100(2).
prepare a Private Generation Study, which assesses distributed and customer-sited resources. Customer
preference resources are also assessed as part of the portfolio selection process. Additional detail can be
found in Volume I, Chapter 8 (Modeling and
100-620(3)(b) utility's load and operations. operations are assessed as part of Volume I, Chapter 8 (Modeling and Portfolio Evaluation). Inputs are
assessed as part of Volume II, Appendix L (Private Generation Study).
100-620(3)(b) process, which is strongly encouraged, IRP should include a summary of the process planning results.
include a if applicable. Also, summaries of our DER planning processes can be found in the conservation potential assessment and private generation studies posted on our website.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100-620(4) generating resources. including renewables, demand-side management, energy storage, distributed energy resources, power purchases, thermal resources, and transmission. Volume I, Chapter 7 (Resource Options) provides relevant detail on conventional generating resources.
100-620(5) considers acquisition of existing and new renewable resources at LRC. evaluated and entered as a model input for the optimal selection of resources. Additional information can be found in Volume I, Evaluation) and Chapter 9 (Modeling and Portfolio
WA-UTC energy storage policy statement (UE-151069 & UE-161024
supply-side resource table, found in Volume I, Chapter 7 (Resource Options). Energy storage potential is assessed as part of Volume II, Appendix N (Energy Storage Potential Evaluation).
100-620(5) integration, and ancillary service technologies. resources are represented in the Supply Resource Table, which is posted on PacifiCorp’s IRP website and included as Volume I, Chapter 7 (Resource Options). All resource types are appropriately subject to integration and ancillary services determination, including transmission upgrade costs, reserve holding capability and additional reserve requirements that are particular to technologies. These factors are
100-620(6) generation and transmission capacity for purposes of delivery of electricity to customers.
availability and price forecasts, which are described and analyzed in Volume I, Chapter 3 (Planning Environment), Chapter 5 (Reliability and Resiliency). Transmission and resource options are described in Volume I, Chapter 4 (transmission)
100-620(6) transmission future needs and the extent and region-based price forecasting, while PacifiCorp's
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No. Requirement How the Guideline is Addressed in the 2023 IRP
transfer capability limitations may affect the future siting of resources. upgrade options. These factors are discussed in the Volume I, Chapter 7 (Resource Options) and Chapter 8 (Modeling and Portfolio
100-620(7) purchasing power or building new resources. competing resources are evaluated to determine each optimal portfolio. Additional information can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and
100-620(7) according to resource costs, including: core functionality of PacifiCorp's optimization modeling. Additional information can be found in Volume I, Chapter 8 (Modeling and Portfolio
100-620(7) costs; firm transmission rights and endogenous transmission upgrade options. Transmission dependencies implying additional resource costs are included in the optimization, resulting in a reasonable comparison of resource costs. Additional information can be found in Volume I, Chapter 7 (Resource Options), Chapter 8 (Modeling and Portfolio Evaluation), and Chapter 9
100-620(7) and the social cost of GHG emissions; three of which were evaluated under a range of additional price-policy conditions. The cases evaluated are described in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
100-620(7) customers, and program participants (when applicable); and requirement differentials, emissions, reserve and load deficiencies, robustness across stochastic variances and additional factors as may emerge from modeling results. In addition to modeling outcomes presented in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), incremental costs relative to the Washington Clean Energy Implementation Plan are discussed in Volume II, Appendix O (Washington Two-Year Progress Report Additional
100-620(7) adopted by WA State or the federal government. process is compliant with all policy requirements. A summary of the policy environment is included as Volume I, Chapter 3 (Planning Environment), and a description of the portfolio runs in compliance with policy is included as Volume I, Chapter 8
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480-
100-620(7) available technologies, or facilities for integrating renewable resources, including but not limited to battery storage and pumped storage, and addressing overgeneration events.
"overgeneration" in dispatch and curtails resources appropriately. These curtailments are an inherent component of the cost and risk valuation of each portfolio, and is a driver for the optimal size, type and location of selected resources.
100-620(8) adequacy metrics. a core model function, where each portfolio is obligated to meet reliability requirements including
varying degrees of quality of operating reserves. This is described in Volume I, Chapter 8
100-620(8)
100-620(8) adequacy metric consistent with prudent utility practice in eliminating coal-fired generation by 12/31/2025 (RCW 19.405.030), attaining GHG neutrality by 1/1/2030 (RCW 19.405.040), and achieving 100 percent clean electricity WA retail sales by 1/1/2045 (RCW
to requirements for the Clean Energy Transformation Act and the Two-Year Progress Report Volume I, Chapter 6 (Load and Resource Balance), Chapter 8 (Modeling and Portfolio Evaluation), and Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year Progress Report Additional Elements).
100-620(9) analysis conducted under RCW 19.405.140, and includes an Company's plan for reporting on metrics related to CBIs.
100-620(9) Company's plan for reporting on metrics related to
100-620(9) populations and highly impacted Company's plan for reporting on metrics related to
100-620(9) health and environmental benefits, Company's plan for reporting on metrics related to
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100-620(9) and environmental risks; and Company's plan for reporting on metrics related to CBIs.
100-620(9) Company's plan for reporting on metrics related to CBIs.
100-620(10) future scenarios and input sensitivities for testing the robustness of the utility's resource portfolio under various parameters, including the following
price-policy futures have been included, as discussed in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
100-620(10) CETA counter factual scenario the alternative LRC and reasonably available portfolio that the utility would have implemented if not for the requirement to comply with RCW 19.405.040 and RCW 19.405.050, as
detail can be found in Volume I, Chapter 8 (Modeling
and Portfolio Evaluation).
100-620(10) Climate change scenario best science available to analyze impacts including, but not limited to, changes in snowpack, streamflow, rainfall, heating and cooling degree days, and load
detail can be found in Volume I, Chapter 8 (Modeling
and Portfolio Evaluation).
100-620(10) Maximum customer benefit sensitivity model the maximum amount of customer benefits described in RCW 19.405.040(8)
detail can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
100-620(11) resource evaluations into a long-range detail can be found in Volume I, Chapter 6 (Load and
100-620(11) describe the resource mix that meets detail can be found in Volume I, Chapter 9 (Modeling
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100- 620(11)(a) explanation of the decisions made, including how the utility's long-range IRP
100- 620(11)(a) coal-fired generation by 12/31/2025 (RCW 19.405.030); Washington’s allocation of electricity by 2025 and will continue to analyze this pending further resolution of interpretive issues by the Commission. Additional information can be found in Volume I,
100- 620(11)(a) (RCW 19.405.040); and information can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results), and Volume II Appendix O (Washington IRP Two-Year
100- 620(11)(a) WA retail sales by 1/1/2045 (RCW 19.405.050) at LRC,
timeline, but is addressed as part of 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year
100- 620(11)(a) WA retail sales by 1/1/2045 (RCW 19.405.050), considering risk. timeline, but the pathway to 2045 is addressed in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year Progress Report
100-
620(11)(c)
preferred portfolio shows pursuit of all
cost-effective, reliable, and feasible conservation and efficiency resources, and
DR.
information can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year
100- 620(11)(d) and I
of existing renewable new resources and
relies on renewable resources and energy storage, insofar as doing so is at LRC,
information can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year
100- 620(11)(d) and (e)
of existing renewable new resources and relies on renewable resources and energy storage, considering risks.
information can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), Chapter 9 (Modeling and Portfolio Selection Results), and Volume II, Appendix O (Washington IRP Two-Year
100-620(11)(f) the safety, reliable operation, and balancing of the utility's electric system, including mitigating over-generation events and achieving identified resource
information can be found in Volume I, Chapter 6 (Load and Resource Balance).
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100- are benefiting from the transition to clean
100- 620(11)(g) nonenergy benefits; reduction of burdens to vulnerable populations and highly IRP Two-Year Progress Report Additional Elements).
100- and environmental benefits; reduction of IRP Two-Year Progress Report Additional
100- Two-Year Progress Report Additional Elements).
100- environmental health impacts to highly Two-Year Progress Report Additional Elements).
100-620(11)(i) DER costs, benefits, and operational characteristics (incl. ancillary services) to and Portfolio Evaluation).
100-620(11)(j) emissions as a cost adder. and Portfolio Evaluation) and Volume II, Appendix O (Washington IRP Two-Year Progress Report
100-620(12) clean energy action plan (CEAP) for implementing RCW 19.405.030 through 19.405.050 at LRC, and at an acceptable resource adequacy standard.

100- year CPA per RCW 19.285.040(1); the IRP Two-Year Progress Report.
100- 620(12)(c) benefiting from the transition to clean energy; the IRP Two-Year Progress Report.
100- 620(12)(d) requirement; level, and the resource adequacy requirement is
explained in Volume I, Chapter 6 (Load and Resource
100- 620(12)(e) and load management programs that may be acquired; (Modeling and Portfolio Selection Results) and Volume II, Appendix O (Washington IRP Two-Year
100-620(12)(f) emitting electric generation, and DERs that may be acquired and evaluate how each identified resource may be expected to contribute to meeting the utility's
PacifiCorp’s resource planning process. Volume I,
Chapter 7 (Resource Options), Chapter 8 (Modeling and Portfolio Evaluation), and Chapter 9 (Modeling
and Portfolio Selection) provide additional detail.
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100- 620(12)(g) expand or upgrade existing, bulk transmission and distribution facilities; Volume I, Chapter 10 (Action Plan).
100- 620(12)(h) which the utility may need to rely on alternative compliance options, if Two-Year Progress Report Additional Elements).
100-620(12)(i) of greenhouse gas emissions as a cost adder equal to the cost per metric ton of carbon dioxide emissions, using the two and one-half percent discount rate, listed in Table 2, Technical Support Document: Technical update of the social cost of carbon (SCC) for regulatory impact analysis under Executive Order 12866, published by the interagency working group on social cost of greenhouse gases of the United States government, August 2016, as adjusted by the Commission to
pricing consistent with DOCKET U-190730 ORDER 03, which updates this specification.
100-620(13) summary of the estimated avoided cost for each supply- and demand-side resource, of the Two-Year Progress Report; however, future determinations of avoided cost will follow the
100-620(13) determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and
100-620(13) values determined through the IRP modeling process.
Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9
100-620(13) determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and
100-620(13) values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9
100-620(13) determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 100-620(13) should specify to which source party they accrue (e.g., utility, customers, participants, vulnerable populations, highly impacted communities, general
Non-Energy Impact Mapping”, as part of the CPA supplemental materials posted on the website, maps the accrual of NEIs to various groups consistent with WAC 480-100-620(13).
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No. Requirement How the Guideline is Addressed in the 2023 IRP
WAC 480- 106-040 used to inform annual purchases of electricity from qualifying facilities, -Year Progress Report; however, future
106-040 used; values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9
106-040 capacity, transmission, distribution, and emissions averaged across the utility; and values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio
106-040 forecasts used in the utility's schedule of estimated avoided cost, including (but not limited to): cost assumptions, production estimates, peak capacity contribution estimates, and annual capacity factor
values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection).
100-620(14) should submit data input files supporting the plan in native file format (e.g.,
supporting spreadsheets in Excel, not PDF
format consistent with practice in prior IRPs.
620(15) electricity from qualifying facilities. Each utility must provide information and analysis that it will use to inform its annual filings required under chapter 480-106 WAC. The detailed analysis must include, but is not limited to, the
620(15)(a) calculate estimates of the avoided cost of energy, capacity, transmission, distribution and emissions averaged
values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter
620(15)(b) forecasts used in the utility's schedule of estimated avoided cost required in WAC 480-106-040 including, but not limited to, cost assumptions, production estimates, peak capacity contribution estimates and annual capacity factor
values determined through the IRP modeling process. Values can be found in Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection).
100-620(16) to modeling methodologies or inputs that change the utility's resource need, as included in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
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Table B.6 – Wyoming Public Service Commission Guidelines
No. Requirement How the Guideline is Addressed in the 2023 IRP

A
The public comment process employed as part of the formulation of the utility’s IRP, including a description, timing and weight given to
PacifiCorp’s public process is described in Volume I, Chapter 2 (Introduction) and in Volume II, Appendix C (Public Input).

B
The utility’s strategic goals and resource planning goals and preferred resource
Volume I, Chapter 9 (Modeling and Portfolio Selection Results) documents the preferred resource portfolio and rationale for selection. Volume I, Chapter 10 (Action Plan) constitutes the IRP action plan and the descriptions of resource strategies and risk management.

C
The utility’s illustration of resource need over the near-term and long-term planning See Volume I, Chapter 6 (Load and Resource Balance).
D A study detailing the types of used for resource portfolio modeling for this IRP.

E
resource acquisitions and load growth from that presented in the utility’s
A comparison of resource changes relative to the 2021 IRP is presented in Volume I, Chapter 10 (Action Plan). A chart comparing the peak load forecasts for the 2019 IRP, and 2021 IRP is included in Volume II, Appendix A (Load Forecast Details).

F
The environmental impacts considered; impacts are considered, including prospective early retirement and gas conversions of existing coal units as alternatives to environmental investments. See Volume I, Chapter 8 (Modeling and Portfolio Evaluation) and Chapter 9 (Modeling and Portfolio Selection) as well
G Market purchases evaluation;
H Reserve Margin analysis; and

I
Demand-side management and conservation options; D (Demand-side Management) for a detailed discussion on DSM and energy efficiency resource options. Additional information on energy efficiency resource characteristics is available

100-620(17)
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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 to achieve
long-term planning objectives. Stakeholders have been involved in the development of the 2023 IRP from the beginning. The public-input meetings held beginning in January 2022 were the cornerstone of the direct public-
input process, and there have been 10 public-input meetings held as part of the 2023 IRP
development cycle. Due to restrictions and concerns surrounding COVID-19, all meetings have been held via phone conference, with no in-person participation. The IRP public-input process also included state-specific stakeholder dialogue sessions held in the
summer of 2022. The goal of these sessions was to capture key IRP issues of most concern to each
state, as well as to discuss how to tackle these issues from a system planning perspective. PacifiCorp wanted to ensure 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 stakeholders in advance of the state meetings. There was additional open time to ensure participants had adequate opportunity for dialogue.
PacifiCorp’s integrated resource plan website houses feedback forms included in this filing. This standardized form allows stakeholders to provide comments, questions, and suggestions. PacifiCorp also posts its responses to the feedback forms at the same location. Feedback forms and PacifiCorp’s responses can be found via the following link:
https://www.pacificorp.com/energy/integrated-resource-plan/comments.html.
Participant List
PacifiCorp’s 2023 IRP continues to be a robust process involving input from many parties. Participants included commissions, stakeholders, and industry experts. Among the organizations that have been represented and actively involved in this collaborative effort are:
Commissions
• California Public Utilities Commission
• Idaho Public Utilities Commission
• Oregon Public Utility Commission
• Public Service Commission of Utah
• Washington Utilities and Transportation Commission
• Wyoming Public Service Commission
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Stakeholders and Industry Experts
• ESS, INC
• Renewable Northwest
• SLC Corp
• Utah Division of Public Utilities
• Western Resource Advocates
• Holland & Hart
• Sierra Club
• Utah Clean Energy
• Interwest Energy Alliance
• Powder River Basin Resource Council
• Northwest Energy Coalition
• Fervo Energy
• Washington Utilities and Transportation Commission
• Renewable Energy Coalition
• Western Energy Storage Task Force
• Enyo
• Apex
• City of Kemmerer Wyoming
• NW Power Council
• Energy Trust of Oregon
• Oregon League of Women Voters
• Oregon Citizen Utility Board
• University of Wyoming
• Applied Energy Group
• Intermountain Wind-Colorado
• Meta
• City of SLC
• Wyoming Energy Consumers
• Wyoming Office of Consumer Advocates
• Powder River Basin Conservation League
• Wyoming Coalition of Local Governments

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PacifiCorp extends its gratitude for the continued time and energy that participants have given to the IRP process. Their participation has contributed significantly to the quality of this plan
As mentioned above, PacifiCorp has hosted 10 public-input meetings, as well as five state meetings during the public-input process, with an additional public-input meeting scheduled for April 2023. During the 2023 IRP public-input process presentations and discussions have covered various issues regarding inputs, assumptions, risks, modeling techniques, and analytical results.
Below are the agendas from the public-input meetings; the presentations can be located at:
https://www.pacificorp.com/energy/integrated-resource-plan/public-input-process.html For the 2023 IRP, all General Public Meeting were held via conference call. The company has initiated making
recording of these meeting publicly available through the IRP website:
General Meetings
February 25, 2022 – General Public Meeting (meeting materials provided to stakeholders on
February 21, 2022)

• Conservation Potential Assessment (CPA)
• 2023 Supply-Side Resources
• 2021 IRP Update / 2023 IRP Overview
• 2023 IRP Public-Input Meeting Schedule

April 7, 2022 – General Public Meeting (meeting materials provided to stakeholders on April 4,
2022)

• Introductions
• 2023 Conservation Potential Assessment (CPA)
• Planning Environment Update
• Optimization Modeling Overview
May 12, 2022 – General Public Meeting (meeting materials provided to stakeholders on May 8,
2022)

• Conservation Potential Assessment
• Request For Proposals Update
• Price Curve Development Update
• Transmission Modeling
• Climate Modeling
June 10, 2022 – Public Meeting (meeting materials provided to stakeholders on June 6, 2022)

• Greenhouse Gas and Renewable Portfolio Standards
• State Policy Update
• Load Forecast Development
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• Interconnection Options
• Supply-Side Resource Alternative Fuels
• 2021 IRP Acknowledgment Update
• Stakeholder Feedback
July 14, 2022 – Public Meeting (meeting materials provided to stakeholders on July 11, 2022)

• Draft Load Forecast Update
• Draft Private Generation Study
• Draft Distribution System Planning
• Renewable Portfolio Standards
• Stakeholder Feedback
• Ozone Transport Rule Update
September 1-2, 2022 – General Public Meeting (meeting materials provided to stakeholders on
August 29, 2022)

Day One
• Inflation Reduction Act
• Supply Side Resource Table
• Existing Thermal Resource Options
• Transmission Modeling
• Price Forecasting
• Customer Preference
• Qualifying Facility Renewal
• Conservation Potential Assessment Draft Results
Day Two
• Conservation Potential Assessment Draft Results—Part II
• Stakeholder Feedback
• Market Reliance Update
• Oregon and Washington Update
• Generation Transition Equity and Justice
• Offshore Wind Workshop
• Hydro Forecasting Under Climate Change October 13, 2022 – General Public Meeting (meeting materials provided to stakeholders on
October 10, 2022)

• Supply-Side Resource Escalation
• Coal and Gas Modeling Options
• Regional Haze Update
• Load Forecast Update
• Transmission Upgrade Options
• Stochastics
• Reliability Assessment
• Portfolio Discussion
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• Stakeholder Feedback Update
December 1, 2022 – General Public Meeting (meeting materials provided to stakeholders on
November 28, 2022)

• Conservation Potential Assessment
• State Allocation and MSP Status Update
• Transmission Interconnection: Cluster Study 2 Results
• Initial Risk and Reliability Study Plan
• State Policy Update
• Stakeholder Feedback Form Update

January 13, 2023 – General Public Meeting (meeting materials provided to stakeholders on
January 10, 2023)

• Extended Day-Ahead Market Update
• 2022 All-Source RFP Update
• Distribution System Planning update
• Transmission and Portfolio Selection Options Update
• Stakeholder Feedback Form Update

February 23, 2023 – General Public Meeting (meeting materials provided to stakeholders on
February 20, 2023)

• Expanded Public Comment Opportunities
• Energy Efficiency Bundling
• Modeling Updates
• Forward Price Curve Updates
• Stakeholder Feedback Update
State-Specific Input Meetings
June 7, 2022 – Oregon State Meeting Part 1 June 7, 2022 – Wyoming State Meeting
June 21, 2022 – Oregon State Meeting Part 2
June 22, 2020 – Washington State Meeting June 29, 2022 – Utah State Meeting July 28, 2022 – Idaho State Meeting
Stakeholder Comments
For the 2023 IRP, PacifiCorp offered a Stakeholder Feedback Form which provided stakeholders
a direct opportunity to provide comments, questions, and suggestions in addition to the opportunities for discussion at 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 and PacifiCorp’s response, can be located on the PacifiCorp website at the IRP
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comments webpage at: www.pacificorp.com/energy/integrated-resource-plan/comments.html. As of March 23, 2023, PacifiCorp has received 36 Stakeholder Feedback Forms (including 4
pending forms) with hundreds of questions, comments, and recommendations. The Stakeholder Feedback Forms have allowed the company to review and summarize issues by topic as well as identify specific recommendations that were provided. Information collected is used to inform the 2023 IRP development process, including feedback related to process improvements and input assumptions, as well as responding directly to stakeholder questions. So far, Stakeholder Feedback
Forms have been received from the following stakeholders:

• ESS, INC
• Renewable Northwest
• SLC Corp
• Utah Division of Public Utilities
• Western Resource Advocates
• Holland & Hart
• Sierra Club
• Utah Clean Energy
• Oregon Public Utilities Commission
• Interwest Energy Alliance
• Powder River Basin Resource Council
• Northwest Energy Coalition
• Fervo Energy
• Washington Utilities and Transportation Commission
• Renewable Energy Coalition
• Western Energy Storage Task Force
A discussion of topics included in the stakeholder feedback forms and how those topics were considered in the IRP are as follows: IRP Public-Input Meeting Process/General Comments Utah Division of Public Utilities submitted feedback stating that PacifiCorp must date its response to stakeholder forms, which the Company will continue to practice as a matter of policy.1 Note that some entries below may appear to anticipate events that have already occurred because they
are presented from the perspective of the responses given at that time.
Legislation A multi-party request asked that PacifiCorp include time and materials in an upcoming 2023 IRP stakeholder presentation to discuss the benefits and opportunities that may be available through
the Infrastructure Investment and Jobs Act, and how they may affect resource and transmission
planning. PacifiCorp emphasized active collaboration with state jurisdictions, as most of the Infrastructure Investment and Jobs Act funds for grid projects will be allocated to each state. 2
1 Feedback Form 007; June 7, 2022 2 Feedback Form 011; July 11, 2022
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Sierra Club submitted a request that PacifiCorp elaborate on the relationship between the Inflation Reduction Act and load forecast assumptions. PacifiCorp responded stating that it has considered
energy efficiency components of IRA for the Conservation Potential Assessment (CPA) by incorporating accelerated adoption rates for certain measure types eligible for IRA rebates and tax credits. It is difficult to exactly prescribe energy efficiency adjustments, but the Company did highlight changes for energy efficiency adoption rates at the December 1st PIM (Public Input Meeting) to reflect the IRA provisions noted in this stakeholder form.3 Load Forecasting Western Resource Advocates recommend modeling two emissions reduction trajectories, in lieu of the “medium” and “high” carbon price scenarios, in addition to the social cost and no-cost GHG
price assumptions.4 The Utah Division of Public Utilities requested an update on the 20-year weather pattern and Bureau of Reclamation Study, citing that the Reclamation study may not represent the most accurate climate change scenario in developing the IRP load forecast for Utah.5
Modeling Assumptions Holland and Hart requested clarification on how PacifiCorp developed the GHG cost methodology and what third party resources were used to develop these costs. PacifiCorp provided this at a
subsequent IRP Public Input Meeting and detailed the source and derivation of its assumptions around the social cost of greenhouse gas and assumptions on price of CO2 that are included in the company’s IRP.6
Western Resource Advocates reiterated the request for information on Jim Bridger modeling,
energy mix disclosure, GHG reporting, natural gas resources and hydrogen updates.7 Salt Lake City Corporation suggested that PacifiCorp evaluates wind and solar generation at an hourly rate vs. using monthly data. The Company acknowledged these limitations and is
continuing to evolve the modeling process. 8
The Oregon Public Utilities Commission requested that PacifiCorp determine the assumptions used on installation of new AC units, conversion rates and how the daily shape of electric vehicle charging is modeled.9

Sierra Club submitted a request inquiring about reliability resources, coal capacity factors. Carbon Capture Utilization and Sequestration (CCUS), load forecast adjustments, Jim Bridger fuel

3 Feedback Form 030; December 7, 2022 4 Feedback Form 012; June 23, 2022 5 Feedback Form 021; September 9, 2022 6 Feedback Form 013; June 27, 2022 7 Feedback Form 015; July 11, 2022 8 Feedback Form 016; July 14, 2022
9 Feedback Form 019; August 5, 2022
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contracts and the Inflation Reduction Act. PacifiCorp responded to this request at length and the response is publicly available on the Company IRP website. 10
Utah Clean Energy submitted a stakeholder request outlining the following questions pertaining to the Lila Canyon coal mine fire including efforts to extinguish the fire, operational and workforce implications, reliability and fuel risk assumptions and impacts to 2023 IRP Plexos modeling. PacifiCorp responded to the request at length and the response is publicly available on the Company IRP website. 11
Natrium Demonstration Project Powder River Basin Resource Council requested updates on Natrium project risk considerations, fuel availability for project longevity and viable waste disposal options. PacifiCorp responded to
this request at length and the information is available to the public online. 12 The Washington Utilities and Transportation Commission submitted feedback noting concerns with the timeline for the release of the 2023 IRP preferred portfolio, modeling updates for the Natrium project following the announcement of a two-year delay and several procedural
observations from IRP Public Input Meeting Series. PacifiCorp responded stating that it is the nature of IRP modeling and preparatory work that results must be confirmed before reporting and that all results are dependent upon ongoing work that is also subject to change. In response to emergent conditions which drive IRP timing, such as federal and state legislation, the Company is providing additional opportunities for public feedback after the March 31st filing and plans to file
an addendum as needed and responsive to stakeholders.13 Natural Gas
Salt Lake City Corporation noted that PacifiCorp should study whether a battery with a grid
forming inverter would provide a lower-cost alternative to natural gas spinning reserves. PacifiCorp outlined its position that it considers a wide range of technologies for supply-side resources14
The Utah Division of Public Utilities outlined potential concerns concerning stranded cost risks
and resource depreciation from conventional natural gas generation and asked to re—evaluate the use of natural gas proxy resources. The Company has since modeled for new natural gas resources in the 2023 IRP.15
Utah Clean Energy submitted feedback asking how PacifiCorp will assess the impacts of methane
leakage mitigation policies on natural gas portfolio outcomes. PacifiCorp responded by stating that the overall impact of the Methane emissions fee is ~1% or less and therefore negligible in the long-term natural gas price forecast16

10 Feedback Form 029; November 28, 2022 11 Feedback Form 031; November 23, 2022 12 Feedback Form 028; October 5, 2022
13 Feedback Form 035; January 17, 2023 14 Feedback Form 009; June 16, 2022 15 Feedback Form 018: July 21, 2022 16 Feedback Form 023; September 8, 2022
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Salt Lake City Corporation submitted feedback insisting that PacifiCorp should consider revising its natural gas price forecast higher in line with the Energy Information Administration short-term
energy outlook. PacifiCorp indicated that the plan is to develop a forecast in September 2022 for use in the 2023 IRP, which will incorporate then-current natural gas prices and the latest long-term expectations. 17 Plexos
Utah Division of Public Utilities Requests Company updates its Supply Side table with current operating and costs characteristics of natural gas fueled generation resources and allow the model to endogenously select natural gas generating resources as proxy resources, as it has done in the past. In the 2021 IRP, PacifiCorp ran an analysis which included options for new gas and for the
2023 IRP, the company has also assessed viable options for the inclusion of new gas in its base modeling. 18 Reliability Assessment
Sierra Club noted several observations pertaining to reliability modeling, the Inflation Reduction Act, and a potential reduction in Transmission costs via the Energy Infrastructure Reinvestment (EIR) program. PacifiCorp responded stating that many of these observations would be fully addressed once the Company provides a comprehensive IRP by the March 31, 2023, filing date.19 Renewable Energy Resources The Renewable Energy Coalition submitted a request outlining PacifiCorp’s compliance with Oregon Public Utility Commission Order No. 22-178 and relevant data including the current QF renewal and success rate at varying capacities. PacifiCorp responded by posting supporting
documentation on the Company Public Input Meeting website titled “QF Extension History”, which provides an inventory of PacifiCorp qualifying facilities with other pertinent information. For supplemental data relating to qualifying facilities, this party was also directed to Oregon dockets LC-77 (2021 IRP) and LC-70 (2019 IRP).20 Resource Adequacy Utah Clean Energy submitted a request that PacifiCorp develop three demand-side management sensitivities utilizing a low, medium, and high method of measurement. With the above feedback considered PacifiCorp instead utilizes a bottom-up modeling approach, which is better suited to
adjustments to inputs for the purpose of informing sensitivities.21
17 Feedback Form 009; June 16, 2022 18 Feedback Form 010; July 7, 2022 19 Feedback Form 034; January 18, 2023 20 Feedback Form 032; January 3, 2023
21 Feedback Form 017; July 21, 2022
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State Energy Policy
Sierra Club requested updates on the Natrium Project, emissions profiles and state policy updates as they relate to the 2021 IRP acknowledgment, greenhouse gas reporting, Renewable Portfolio Standards, load forecast updates and compliance with the Washington Clean Energy Transformation Act (CETA).22
Washington Utilities and Transportation Commission Staff emphasized the statutory obligation for Washington utilities to incorporate the social cost of greenhouse gas into Washington allocated resource carbon cost assumptions. PacifiCorp responded by stating it is not aware of any language in RCW 19.280.030(3) and WAC 480-100-605 that requires utilities to include the SCGHG as their base carbon cost price-policy assumption for Washington-allocated resources.23
Supply-side Resource Costs/Supply-side Resource Table ESS Inc requested an update from PacifiCorp on what changes are being made to the IRP modeling to determine marginal values of long-duration flow battery storage. The Company informed this
party that it is commissioning a study of the cost and performance characteristics of energy storage and expects the study to include information specific to long duration flow batteries24 Renewable Northwest submitted a request that PacifiCorp consider DC-coupled solar + storage as well as other additional battery storage durations (medium and long-duration) as part of the supply-
side resource table and subsequent IRP modeling. The Company responded indicating that Proxy resource modeling in the 2023 IRP is intended to be representative of costs and operational characteristics across a range of configurations and at this time is based on AC configuration but does not preclude other constructs from participating in all-source requests for proposals. 25

Fervo Energy submitted a supply-side resources feedback outlining new cost assumptions that geothermal is becoming a less cost-prohibitive resource option that has the potential to create new jobs. In line with regulatory precedent, PacifiCorp remains committed to pursuing least- cost, least-risk preferred portfolio outcomes including geothermal when economically competitive.26

Renewable Northwest submitted feedback requesting updated transmission capacity metrics, offshore wind costs and recent modeling assumptions. PacifiCorp responded by stating that it has added 1,000 MW of offshore wind resources to the supply-side table among other more detailed information provided in this stakeholder form. 27

The Western Energy Storage Task Force recommended the use of a specified forecast for utility-scale battery storage resources and proposed revising price modifications. PacifiCorp responded and re-affirmed that the costs presented in the September 1st Public Input Meeting do not include tax incentives implemented in the Inflation Reduction Act. Additional supply-side table reporting
22 Feedback Form 014; July 1, 2022 23 Feedback Form 024; September 20, 2022
24 Feedback Form 001; February 24, 2022 25 Feedback Form 002; March 3, 2022 26 Feedback Form 020; August 23, 2022 27 Feedback Form 022; September 14, 2022
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will identify costs after accounting for tax incentives and all tax incentives are being accounted for in the 2023 IRP modeling process. The information about tax incentives presented to date is consistent with Table 7.1 in PacifiCorp’s 2021 IRP. Resource information inclusive of tax
incentives was provided in Table 7.2 of PacifiCorp’s 2021 IRP and comparable information will be provided for the 2023 IRP.28 Salt Lake City Corporation submitted a request for the inclusion of a supply-side long-duration storage option with characteristics similar to the iron air battery announced earlier in the year. The
Company responded by stating that it is considering longer duration energy storage similar to Form Energy Iron Air Battery in the 2023 IRP. PacifiCorp is commissioning a study of the cost and performance characteristics of energy storage and expects the study to include cost information specific to long duration flow batteries.29 Transmission The Utah Division of Public Utilities requested supplemental study information and transmission topology, specifically referring to the Kiewit study on natural gas and hydrogen and requesting further information regarding why the Jim Bridger coal plant was moved to the PAC-east
balancing authority. PacifiCorp responded directly to this stakeholder request and did not publish the response due to sensitivities around the Kiewit study. The Interwest energy alliance inquired about whether or not PacifiCorp reviews the potential for reconductoring with advanced conductors, grid enhancing technology or advanced transmission
technologies. PacifiCorp responded by saying it considers reconductoring with advanced conductors such as ACCC and ACSS if this provides a solution to thermal issues that are observed during outage conditions for regular studies such as Cluster Studies, Transmission Planning Assessment studies TPL001-4 and others30
Contact Information
PacifiCorp’s IRP website: w ww.pacificorp.com/energy/integrated-resource-plan.html.

PacifiCorp requests any informal request be sent to the following address or email. PacifiCorp IRP Resource Planning Department
825 N.E. Multnomah, Suite 600
Portland, Oregon 97232 Email Address: I [e-mail]

28 Feedback Form 027; October 27, 2022 29 Feedback Form 003; May 12, 2022
30 Feedback Form 033; January 10, 2023
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PACIFICORP – 2023 IRP APPENDIX D – DEMAND-SIDE MANAGEMENT RESOURCES

103

APPENDIX D – DEMAND-SIDE MANAGEMENT
Introduction
This appendix reviews the studies and reports used to support the demand-side management (DSM) resource information used in the modeling and analysis of the 2023 Integrated Resource Plan (IRP). In addition, it provides information on the economic DSM selections in the 2021 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.
Conservation Potential Assessment (CPA) for 2023-2042
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 Conservation Potential Assessment (CPA) for 2023-2042,1 conducted by Applied Energy
Group (AEG) on behalf of PacifiCorp, primarily seeks to develop reliable estimates of the magnitude, timing, and costs of DSM resources likely available to PacifiCorp over the IRP’s 20-year planning horizon. The study focuses on resources realistically achievable during the planning horizon, given normal market dynamics that may hinder or advance resource acquisition. Study
results were incorporated into PacifiCorp’s 2023 IRP and will be used to inform subsequent DSM
planning and program design efforts. This study serves as an update of similar studies completed since 2007. For resource planning purposes, PacifiCorp classifies DSM resources into four categories,
differentiated by two primary characteristics: reliability and customer choice. These resource
classifications can be defined as: demand response (e.g., a firm, capacity focused resource such as direct load control), energy efficiency (e.g., a firm energy intensity resource such as conservation), demand side rates (DSR) (e.g., a non-firm, capacity focused resource such as time of use rates), and behavioral-based response (e.g., customer energy management actions through education and
information).
From a system-planning perspective, demand response resources can be considered the most reliable, as they can be dispatched by the utility. In contrast, behavioral-based resources are the least reliable due to the resource’s dependence on voluntary behavioral changes. With respect to
customer choice, demand response and energy efficiency 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. DSR and behavioral-based activities involve greater customer

1 PacifiCorp’s Demand-Side Resource Potential Assessment for 2023-2042, completed by AEG, can be found at: www.pacificorp.com/energy/integrated-resource-plan/support.html.
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choice and control. This assessment estimates potential from demand response, energy efficiency,
and DSR. The CPA excludes an assessment of Oregon’s energy efficiency resource potential, as this work is performed by Energy Trust of Oregon, which provides energy efficiency potential in Oregon to
PacifiCorp for resource planning purposes.
Current DSM Program Offerings by State
Currently, PacifiCorp offers a robust portfolio of DSM programs and initiatives, most of which are offered in multiple states, depending on size of the opportunity and the need. Programs are reassessed on a regular basis. PacifiCorp has the most up-to-date programs on its website.2 Demand response and energy efficiency program services and offerings are available by state
and sector. Energy efficiency services listed for Oregon, except for low-income weatherization
services, are provided in collaboration with Energy Trust of Oregon.3
Table D.1 provides an overview of the breadth of demand response and energy efficiency program services and offerings available by Sector and State.

PacifiCorp has numerous DSR offerings currently available. They include metered time-of-day and time-of-use pricing plans (in all states, availability varies by customer class), and residential seasonal rates (Idaho and Utah). System-wide, approximately 16,100 customers were participating in metered time-of-day and time-of-use programs as of December 31, 2022.

Savings associated with rate design are captured within the company’s load forecast and are thus captured in the integrated resource planning framework. PacifiCorp continues to evaluate DSR programs for applicability to long-term resource planning.
PacifiCorp provides behavioral based offerings as well. Educating customers regarding energy
efficiency and load management opportunities is an important component of PacifiCorp’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 behavioral activity will show up in demand response
and energy efficiency 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.

2 Programs for Rocky Mountain Power can be found at www.rockymountainpower.net/savings-energy-choices.html
and programs for Pacific Power can be found at www.pacificorp.com/environment/demand-side-management.html. 3 Funds for low-income weatherization services are forwarded to Oregon Housing and Community Services.
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Table D.1– Current Demand Response and Energy Efficiency Program Services and Offerings by Sector and State
Program Services & Offerings by Sector and State California Oregon Washington Idaho Utah Wyoming
Residential Sector
Air Conditioner Direct Load Control √
√ √ √ √ √ √
√ √ √ √ √ √
√ √ √ √ √ √
Windows, Insulation, Duct √ √ √ √ √ √
√ √ √ √ √ √
√ √ √ √ √ √
√ √ √ √ √
√ √ √
√ √
Trade Ally Outreach √ √ √ √ √ √

Program Services & Offerings by Sector and State California Oregon Washington Idaho Utah Wyoming
Non-Residential Sector
Irrigation Load Control √ √ √ √
Commercial and Industrial Demand Response √ √ √
√ √ √ √ √ √
√ √ √ √ √ √
√ √ √
Energy Management √ √ √ √ √ √
Energy Profiler Online √ √ √ √ √ √
Business Solutions Toolkit √ √ √ √ √ √
Trade Ally Outreach √ √ √ √ √ √
Small Business Lighting √ √ √ √ √
Lighting Instant Incentives √ √ √ √ √ √ Small to Mid-Sized Business Facilitation √ √ √ √ √ √
With Customer Account √ √ √ √ √ √

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Table D.2 – Current Wattsmart Outreach and Communications Activities
Communications (incremental to program specific California Oregon Washington Idaho Utah Wyoming
Advertising √ √ √ √ √
Sponsorships √ √
Social Media √ √ √ √ √ √
Public Relations √ √ √ √ √
Business Advocacy (awards at customer meetings, sponsorships, chamber partnership, university √ √ √ √ √ √
√ √ √ √ √ √
wattsmart √ √ √ √
State-Specific DSM Planning Processes
A summary of the DSM planning process in each state is provided below. 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, development of multi-year DSM plans, program marketing, incentive levels, budgets, adaptive management, and the development of new and pilot programs. 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 that advises on a wide 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. PacifiCorp works with the
conservation stakeholder group annually on its energy efficiency program design and planning. In 2019, Washington passed the Clean Energy Transformation Act (CETA), which requires utilities to meet three primary clean energy standards: remove coal-fueled generation from
Washington’s allocation of electricity by 2025, serve Washington customers with greenhouse gas
neutral electricity by 2030, and to serve customers in Washington with 100% renewable and non-emitting electricity by 2045. The conservation stakeholder group and the demand-side
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management advisory group inform the CETA planning process as documented in the Company’s Clean Energy Implementation Plan (CEIP)4. California On December 19, 2022, the Commission issued approved the company’s Biennial Budget Advice Letter (BBAL) Filing 697E to administering its energy efficiency programs through 2024. The BBAL was submitted PacifiCorp submitted in accordance with Ordering Paragraph 4 of Decision
(D.) 21-12-034 an application for the continuation of energy efficiency programs for program years 2022-2026 on December 31, 2020. Oregon
Energy efficiency programs for Oregon customers are planned for and delivered by Energy Trust
of Oregon in collaboration with PacifiCorp. 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.
Preferred Portfolio DSM Resource Selections
The following tables show the economic DSM resource selections by state and year in the 2023
IRP preferred portfolio5.

4 The Company’s CEIP can be found online at https://www.pacificorp.com/content/dam/pcorp/documents/en/pacificorp/energy/ceip/PAC-CEIP-12-30-
21_with_Appx.pdf 5 Following DSM resource selection methodologies described in Chapter 7 of the IRP.
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Table D.3 –First Year Demand Response Resource Selections (2023 IRP Preferred Portfolio)6

Table D.4 – First Year Energy Efficiency Resource Selections (2023 IRP Preferred Portfolio)

For the 20-year assumed nameplate capacity contributions (MW impacts) by state and year associated with the energy efficiency resource selections above, see Volume I, Chapter 9
(Modeling and Portfolio Selection).

6 A portion of cost-effective demand response resources identified in the 2023 preferred portfolio in 2023 for
Oregon and Washington represent planned volumes expected to be acquired in 2023 PacifiCorp will pursue all cost-effective demand response resources identified as incremental to resources offered through approved programs.
Resource 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032
DR Summer - ID 0.0 0.0 4.1 9.0 5.7 1.0 0.3 0.3 0.3 0.0
DR Summer - UT 0.0 8.5 27.6 23.3 28.7 20.6 12.1 10.6 13.9 0.0
DR Summer - WY 0.0 0.0 14.3 0.9 21.8 3.5 0.1 0.0 0.1 0.0
DR Winter - ID 0.0 0.4 1.0 1.1 0.6 0.2 0.0 0.0 0.0 0.0
DR Winter - UT 0.0 0.5 6.7 5.6 1.7 1.9 0.0 0.0 0.0 0.0
DR Winter - WY 0.0 0.0 9.8 14.3 7.3 4.3 0.4 0.5 0.3 0.0
DR Summer - CA 0.0 0.0 2.7 1.5 1.4 0.5 0.1 0.1 0.2 0.0
DR Summer - OR 47.0 1.9 33.5 20.6 44.6 16.0 12.3 4.0 5.5 0.0
DR Summer - WA 24.5 2.9 7.3 7.5 10.7 3.7 2.0 0.0 1.8 0.0
DR Winter - CA 0.0 0.0 1.2 1.7 0.3 1.1 0.0 0.0 0.0 0.0
DR Winter - OR 0.0 14.7 37.0 20.2 9.0 23.3 0.0 0.0 0.0 0.0
DR Winter - WA 0.0 9.7 7.1 3.6 1.2 5.1 0.0 0.0 0.0 0.0
Resource 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
DR Summer - ID - - - - - 37.3 0.4 0.3 - -
DR Summer - UT - - - - - 113.2 14.8 15.5 - -
DR Summer - WY - - - - - 7.4 0.1 0.1 - -
DR Winter - ID - - - - - - - - - -
DR Winter - UT - - - - - - - - - -
DR Winter - WY - - - - - 0.4 - - - -
DR Summer - CA - - 0.2 0.0 - 3.8 0.1 0.1 - -
DR Summer - OR - - 3.6 0.0 0.0 57.3 3.3 3.0 - -
DR Summer - WA - - 0.8 - - 13.2 0.7 0.5 - -
DR Winter - CA - - - - - - - - - -
DR Winter - OR - - - - - - - - - -
DR Winter - WA - - 2.4 - - - - - - -
Energy Efficiency Energy (1st Year Savings MWh) Selected by State and Year
State 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032
CA 2,425 2,704 3,033 3,503 4,200 4,703 4,540 3,623 4,292 3,093
OR 164,891 188,547 198,401 157,042 169,924 165,387 128,721 138,568 187,201 96,943
WA 53,112 39,612 48,328 32,771 37,248 41,527 41,936 42,014 42,060 38,434
UT 266,500 266,661 273,564 292,860 318,621 348,920 421,605 434,966 722,976 286,797
ID 12,000 14,884 17,573 21,828 24,912 26,756 28,528 28,069 34,929 22,065
WY 44,204 38,468 55,003 55,087 58,854 59,351 66,738 69,934 93,500 61,036
Total System 543,132 550,876 595,902 563,091 613,759 646,644 692,068 717,174 1,084,958 508,368
Energy Efficiency Energy (1st Year Savings MWh) Selected by State and Year
State 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
CA 2,968 2,941 2,712 4,291 5,027 4,365 3,931 3,088 1,045 1,369
OR 113,012 116,620 70,673 89,040 157,073 85,104 84,261 58,890 31,439 150,622
WA 37,560 36,741 35,895 35,228 35,735 30,881 27,574 27,252 17,639 16,641
UT 324,918 335,953 351,377 486,426 753,213 307,927 344,013 376,481 382,259 513,035
ID 26,134 28,410 29,288 30,150 29,760 23,177 21,277 22,636 20,693 17,551
WY 59,034 61,187 59,279 81,096 74,415 50,116 46,386 54,210 39,728 68,544
Total System 563,626 581,852 549,224 726,231 1,055,223 501,570 527,442 542,557 492,803 767,762
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APPENDIX E – SMART GRID
Introduction
Smart grid is the application of advanced communications and controls to the electric power
system. As such, a wide array of applications can be defined under the smart grid umbrella. PacifiCorp has identified specific areas for research that include technologies such as dynamic line rating, phasor measurement units, distribution automation, advanced metering infrastructure (AMI), automated demand response and other advanced technologies. PacifiCorp has reviewed relevant smart grid technologies for transmission and distribution systems that provide local and
system benefits. When considering these technologies, advanced controls and communications often the most critical infrastructure decision. This network must have relevant speed, reliability, and security to support applications such as current real-time WEIM (optimizes the energy imbalances throughout the West) by transferring energy between participants in 15-minute and 5-minute intervals throughout the day.
PacifiCorp has planned to build on the success of real-time energy market innovation by joining the new Western day-ahead market, (EDAM), developed by the California Independent System Operator (CAISO). A modernized western energy market is a key component of PacifiCorp’s strategy to connect and optimize the West’s abundant and diverse energy resources to deliver the
lowest cost and most reliable pathway to a net-zero energy future. PacifiCorp is committed to advancing innovation in markets and new energy technologies to meet its commitment to affordability and reliability while supporting its communities throughout the energy transition. PacifiCorp has focused on those technologies that present a positive benefit for customers and has
implemented functions such as advanced metering, dynamic line rating, and distribution automation. 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 for integration when they are found to be appropriate investments. The company 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 can improve cost estimates and benefits of smart grid technologies that will assist in identifying the best suited technologies for implementation.
Transmission Network and Operation Enhancements
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 online-loading calculations given a set of worst-case weather assumptions, such as high ambient temperatures and very low wind speeds. Dynamic line rating (DLR) allows an
increase in current-carrying capacity of transmission lines, when more favorable weather
conditions are present, a without compromising safety. DLR has become increasingly relevant with higher shares of variable renewable energy (VRE) in the power system. By seeking to increase the ampacity of transmission lines, it provides economic and technical benefits to all
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involved. FERC NOPR (RM21-17-000) is calling to fully consider dynamic line ratings and advanced power flow control devices in local and regional transmission planning processes. PacifiCorp has been using DLR since 2014. The Standpipe-Platte project was implemented in 2014
and has delivered positive results as windy days are directly linked to increased wind power generation and increased transmission ratings. A dynamic line rating system is used 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 Standpipe-Platte 230 kilovolt (kV) transmission line is one of three lines in the Aeolus West transmission corridor and had been one of the lines that
limits the corridor power transfer. As a result of this project, the Aeolus West Western Electricity Coordinating Council (WECC) non-simultaneous path rating was increased. The DLR system on the Platte – Standpipe 230 kV line has been updated with a Transmission Line Monitoring (TLM) system manufactured by Lindsey Systems.
Additionally, a new DLR system is being implemented on the existing Dave Johnston- Amasa – Difficulty – Shirley Basin 230 kV line as part of the Gateway Segment D.1 Project. The Dave Johnston- Amasa – Difficulty – Shirley Basin 230 kV line connects two areas with a high penetration of wind generation resources and implementation of the DLR system will improve the link between those two areas to reduce the need for operational curtailments when wind patterns
result in a variation in generation between the two areas, such as high winds in the northeast area and moderate to low winds in the southeast area. The DLR system will increase the transmission line steady-state rating under increased wind conditions and reduce instances and duration of associated generation curtailments.
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, and it may or may not align with expected transmission needs of future projects. PacifiCorp will continue to look for opportunities to cost-effectively employ dynamic line rating
systems similarly to the one deployed on the Standpipe – Platte 230 kV transmission line... Digital Fault Recorders / Phasor Measurement Unit Deployment To meet compliance with the North American Electric Reliability Corporation (NERC) MOD-033-1 and PRC-002-2 standards, PacifiCorp has installed over 100 multifunctional digital fault
recorders (DFR) which include phasor measurement unit (PMU) functionality. The installations
are at key transmission and generation facilities throughout the six-state service territory, generally
placed on WECC identified critical paths. PMUs provide sub-second data for voltage and current
phasors, which can be used for MOD-033-1 event analysis and model verification. DFRs have a
shorter recording time with higher sampling rate to validate dynamic disturbance modelling per
PRC-002-2. The DFR/PMUs will deliver dynamic PMU data to a centralized phasor data
concentrator (PDC) storage server where offline analysis can be performed by transmission
operators, planners, and protection engineers to validate system models has been completed.
Transmission planners will use the phasor data quantities from actual system events to benchmark
performance of steady-state and transient stability models of the interconnected transmission
system and generating facilities. Using a combination of phasor data from the PMUs and analog quantities currently available through Supervisory Control and Data Acquisition System (SCADA), transmission planners can set up the system models to accurately depict the transmission system prior to, during, and following an event. Differences in simulated versus
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actual system performance will then be evaluated to allow for enhancements and corrections to the system model. Model validation procedures are being evaluated, in conjunction with data and equipment
availability to fulfill MOD-033-1. The process of validating the system model against a historical system outage event that includes the comparison of a planning power flow model to actual system behavior and the comparison of the planning dynamic model to actual system response is ongoing. PacifiCorp will continually evaluate potential benefits of PMU installation and intelligent
monitoring as the industry considers PMU in special protection, remedial action scheme and other roles that support transmission grid operators. PacifiCorp will continue to work with the California Independent System Operator’s (CAISO) Reliability Coordinator West to share data as appropriate.
Distribution Automation and Reliability
Distribution Automation
Distribution automation encompasses a wide field of smart grid technology and applications that
focus on using sensors and data collection on the distribution system, as well as automatically adjusting the system to optimize performance. Distribution automation can also provide improved outage management with decreased restoration times after failure, operational efficiency, and peak load management using distributed resources and predictive equipment failure analysis using
complex data algorithms. PacifiCorp is working on distribution automation initiatives focused on
improved system reliability through improved outage management and response. In Oregon, PacifiCorp identified 40 circuits on which cost benefit analyses were performed. From this analysis two circuits in Lincoln City, Oregon were selected to have a fault location, isolation and service restoration (FLISR) system installed. The project was installed through 2019 and
commissioning of the automation scheme conducted through 2020 in the distribution loop out of
Devil’s Lake substation in Lincoln City, Oregon. The Company also moved its pre-deployment distribution automation testing equipment to its Tech Ops center in Portland, Oregon to expand open discussion between internal end users including operations, service crews and field technicians. Throughout the implementation of the Devil’s Lake DA scheme, the Company faced
persistent challenges with communication over its existing AMI network. The Company found the
communication capability of AMI was not suited well for a FLISR scheme and evaluated alternative solutions. The solution now uses fiber optic communication, which the Company installed in a loop configuration to increase resiliency of the FLISR scheme’s communication path. The fiber infrastructure was deployed in Q4 2022, and the Company now has complete FLISR
capability with the Devil’s Lake DA system.
Based on that experience additional two additional automation projects were initiated in Portland and Medford, relying on private fiber optic communications (in a manner very similar to how transmission assets would be monitored) Engineering and construction are in progress and
commissioning during 2022 is anticipated.

Distribution Substation Metering
Substation monitoring and measurement of various electrical attributes were identified as a
necessity due to the increasing complexity of distribution planning driven by growing levels of primarily solar generation as distributed energy resources. Enhanced measurements improve
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visibility into loading levels and generation hosting capacity as well as load shapes, customer usage patterns, and information about reliability and power quality events. In 2017, an advanced substation metering project was initiated to provide an affordable option for
gathering required substation and circuit data at locations where SCADA is unavailable and/or uneconomical. SCADA has been the preferred form of gathering load profile data from distribution circuits, however SCADA systems can be expensive to install, and additional equipment is required to provide the data needed to perform distribution system and power quality analysis. When system data rather than data and control is important, SCADA is no longer the best option.
Engineers require data to perform analysis of system loading and diagnose waveform and harmonics issues; the lack of data can inhibit accurate system evaluations. The substation metering project recognizes that system data has value independent of control and current system status. The advanced substation metering pilot is intended to provide an affordable option for gathering
required distribution system data. The advanced substation metering project was intended to provide an affordable option for
gathering required distribution system data. The Company’s work plan included:
• Finalize installation of advanced substation meters at distribution substations and
document installations
• Ensure all substation meters installed as part of this program are enabled with remote
communication capabilities
• Refine a data management system (PQView) to automatically download, analyze and
interpret data downloaded from all installed substation meters

The advanced substation metering project enabled installation of enhanced monitors at more than
fifty distribution circuits in the state of Utah. The Company also deployed PQView software, a
data analytics tool that provides users with a refined view of power quality information gathered
from substation meters.
Distributed Energy Resources
Energy Storage Systems In 2017, PacifiCorp filed the Energy Storage Potential Evaluation and Energy Storage Project proposal with the Public Utilities Commission or Oregon. This filing was in alignment with
PacifiCorp’s strategy and vision regarding the expansion and integration of renewable
technologies. The company proposed a utility-owned targeted energy storage system (ESS) pilot project. In 2019 PacifiCorp began project development and is progressing to build an ESS on a Hillview substation distribution circuit in Corvallis, Oregon. Due to issues finding a suitable location in Corvallis the company located a different location. The new location for the ESS is the
Lakeport Substation in Klamath Falls. The intent of this project is to integrate the ESS into the
existing distribution system with the capability and flexibility to potentially advance to a future micro grid system. Phase I of the project involves/involved installation of a single, utility-owned energy storage
device to address historic outage characterization on a specific feeder, validate modeling through
field test data, create a research platform and optimize energy storage controls and integration on the Company network. The Company contracted an owner’s engineer to aid in project development and is progressing on the Phase I project to build an ESS at the Oregon Institute of Technology
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(OIT) on circuit SL49, fed from the Lakeport substation. The Company contracted Powin Energy to provide the ESS. The intent of this project is to integrate the ESS into the existing distribution system with the capability and flexibility to potentially provide renewables integration support with OIT’s solar generation. The minimum system size is:
• Energy requirement of 6 MWh • Power requirement of 2 MW Phase II of the project involves/involved the addition of an additional energy storage device to pilot distributed storage, optimize use cases per Phase I results, explore tariff structure and
ownership models and continue research. In 2020, PacifiCorp developed Community Resiliency programs in Oregon and California to expand customer and utility understanding of how the use of ESS equipment might increase the resilience of critical facilities. The initial pilot programs provided technical support and evaluation
of potential options as well as grant funding for on-site battery storage systems. Over one dozen feasibility studies have been delivered across the service territory of the two states. Two ESS systems have been installed in California with a third approved; two grant submissions in Oregon are in the final stage of application approval. As part of the Company’s forthcoming first Clean Energy Plan (CEP) with the Oregon Public Utilities Commission. PacifiCorp presented a strawman
proposal to expand the Oregon pilot into a larger program that could provide grant funding for the installation of solar as well as battery storage. The Program would continue to provide feasibility studies and technical support to interested facilities. The Company plans to elicit feedback on the proposal through CEP stakeholder channels and determine next steps by the end of 2023. The PacifiCorp filing with FERC covering optional generation interconnection study assumptions
for stand-alone electric storage resources was approved on February 28, 2023 (section 38.1 of the
Open Access Transmission Tariff). The use of real-world operating assumptions for electric
storage resources should lead to a more efficient interconnection process.
Demand Response In 2018, PacifiCorp transitioned to the automatic dispatch of the residential air conditioner (A/C) program in Utah, utilizing two-way communication devices to respond to frequency dispatch signals. Known as Cool Keeper this frequency dispatch innovation is a grid-scale solution using
fast-acting residential demand response resources to support the bulk power system. Some utilities
use generating resources to perform this function, but as higher levels of wind and solar resources are added, additional balancing resources are required. The Cool Keeper system provides over 200 MWs of operating reserves to the system through the control of more than 108,000 A/C units.
In 2021, PacifiCorp released a Request for Proposals for Demand Response resources. The
Company has used the responses to incorporate the cost of Demand Response programs more accurately in the 2021 Integrated Resource Plan. In 2022 and 2023, PacifiCorp contracted with vendors solicited during the demand response RFP and filed for programs in Oregon, Washington, Idaho, Utah, and Wyoming. These programs included new Irrigation and Commercial and
Industrial curtailment programs. Dispatchable Customer Storage Resources Based on the learnings from Rocky Mountain Power’s partnership with Soleil Lofts and Sonnen in 2018, the company developed the Wattsmart Battery Program which was approved in Utah
October 2020 and in Idaho April 2022. This innovative demand response program allows the
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Company to manager behind the meter customer batteries for daily load cycling, backup power
real time grid needs such as peak load management, contingency reserves, and frequency response.
Customer controlled batteries will allow the company to maximize renewable energy when it’s
needed to support the electrical gird. The program is experiencing exponential growth and has over 2,700 residential batteries and 8 commercial batteries participating as of Q1 2023.
Advanced Metering Infrastructure
Advanced metering infrastructure (AMI) is an integrated system of smart meters, communications networks, and data management systems that provide interval data available daily. This infrastructure can also provide advanced functionalities including remote connect/disconnect, outage detection and restoration signals, and support distribution automation schemes. In 2016,
PacifiCorp identified economical AMI solutions for California and Oregon that delivered tangible
benefits to customers while minimizing the impact on consumer rates. In 2019, PacifiCorp completed installation of the Itron Gen5 AMI system across the Company’s
Oregon and California service territories. The AMI system consists of head-end software, FANs
and approximately 656,000 meters. Interval energy usage data is provided to customers via the
Pacific Power website and mobile app. The project was completed on schedule and on budget.

In 2018, PacifiCorp awarded a contract to Itron for their OpenWay Riva AMI system in the states
of Idaho and Utah. In early 2020, Itron proposed a change for the information technology (IT) and
network systems, using their Gen5 system rather than the OpenWay system, while still deploying
the more advanced Riva meter technology. Itron’s Gen5 system has the same IT and network used
in PacifiCorp’s Oregon and California service territories. This solution aligns with Itron’s future
road map and provides PacifiCorp with a single operational system that will reduce cybersecurity
issues and operating costs associated with maintaining separate systems. This solution provides a
stronger, more flexible network coupled with a high-end metering solution.

The Utah/Idaho project involves upgrading the head-end software and installation of the Field Area
Network (FAN) and approximately 240,000 new Itron Riva AMI meters for most customer
classification and 20,000 Aclara AMI meters for the Utah rate schedule 136 private generation
accounts. This solution will utilize over 80% of the existing AMR meters in Utah to provide hourly
interval data for residential customers as well as outage detection and restoration messaging. The
project will replace all current meters in Idaho with new Itron Riva AMI meters as AMR was not
fully deployed there. Furthermore, the project will leverage the customer communication tools
developed for the Oregon and California AMI projects.

Meter and FAN system installations in Idaho are substantially complete. Utah FAN and meter
installations are underway with completion scheduled for Q4 2023. Costs and benefits associated
with the AMI project will be tracked and analyzed and will be evaluated against the business case
projections after completion.

Financial analyses to extend AMI solutions to Washington and Wyoming were performed in 2019
and 2020, respectively. The analyses determined that moving these states to an AMI solution was
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not cost effective at this time. The Company is currently updating the business case for both states.
The review should be completed by Q2 2023.

Financial analyses to extend AMI solutions to Washington and Wyoming were performed in 2019 and 2020, respectively. These states utilize the same AMR meter technology as Utah and can be leveraged to provide extended functionality and value. The analyses determined that moving these
states to an AMI solution is not cost effective at this time but has improved slightly over previous
analyses. The Company will continue to review and evaluate the business case and cost
effectiveness for these states routinely over the next few years.
Outage Management Improvements
PacifiCorp advanced a new module in its OMS which allows for field responders to update outage data as they complete their work, using Mobile Workforce Management tools; this functionality is restricted to service transformer and customer meter devices, which comprise approximately half
of the outages to which the company responds. This ensures more rapid, accurate and efficient
updates to outage data, but still maintains the OMS topology as the method to manage line worker safety by having real-time access to elements that are energized and those which may be in an abnormal state. Meter pinging and last-gasp outage management functionalities were put in place for the AMI
system in Oregon and California. The same outage management systems (OMS) will be used for
Utah and Idaho when those projects are complete. Company’s system operations organization has begun using meter ping functionality and last-gasp messages to augment customer calls and create outage tickets in the Company’s OMS. The Company implemented business process changes to facilitate outage management functionality for single service as well as large-scale outages. These
changes have provided the system operations with more flexibility to identify and respond to
outages. The intelligent line sensors will be installed on distribution circuits that will provide service to critical facilities. For this project, critical facilities have been defined as major emergency facility centers such as hospitals, trauma centers, police, and fire dispatch centers, etc. The information
provided by the line sensors will allow control center operators to target restoration at critical
facilities during major outages sooner than is currently possible. Full implementation of the project is was completed in December 2021, concurrent with the completion of the AMI project.
Future Smart Grid
The Company continues to develop a strategy to attain long-term goals for grid modernization and
smart grid-related activities to continually improve system efficiency, reliability, and safety, while
providing a cost-effective service to our customers. The Company will continue to monitor smart
grid technologies and determine viability and applicability of implementation to the system, and
as tipping points to broader implementation occur it’s expected these will be communicated
through a variety of methods, including this IRP as well as other regulatory mechanisms relevant
to that state.

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APPENDIX F – FLEXIBLE RESERVE STUDY
Introduction
While PacifiCorp had significant increases in both wind and solar capacity on its system in 2021, there has not yet been time to collect and assess sufficient historical data that includes this
expanded output. Therefore, for the 2023 IRP, PacifiCorp is continuing to use the methodology
developed in its 2021 Flexible Reserve Study (FRS), which relied upon historical data from 2018-2019, as discussed below.1 The 2021 Flexible Reserve Study (FRS) estimated the regulation reserve required to maintain
PacifiCorp’s system reliability and comply with North American Electric Reliability Corporation
(NERC) reliability standards. Because the FRS methodology accounts for changes in PacifiCorp’s resource mix, both the quantity and cost of reserves has been updated for the 2023 IRP, as reported herein.
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-001-2,2 as well as the amount of
contingency reserve required to comply with NERC standard BAL-002-WECC-2.3 BAL-001-2 is a regulation reserve standard that became effective July 1, 2016, and BAL-002-WECC-3 is a contingency reserve standard that became effective June 28, 2021. 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.”4 Apart from disturbance events that are addressed through contingency reserve, regulation reserve is necessary to compensate for changes in load demand and generation output 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 resources5

1 2021 IRP Volume II, Appendix F (Flexible Reserve Study): https://www.pacificorp.com/content/dam/pcorp/documents/en/pacificorp/energy/integrated-resource-plan/2021-irp/Volume%20II%20-%209.15.2021%20Final.pdf
2 NERC Standard BAL-001-2, https://www.nerc.com/pa/Stand/Reliability%20Standards/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. 3 NERC Standard BAL-002-WECC-3, https://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-002-WECC-3.pdf, which became effective June 28, 2021. BAL-002-WECC-3 removed the requirement that at least 50% of contingency reserves be held as “spinning” resources, as this was deemed redundant with frequency response requirements under BAL-003-2. 4 Glossary of Terms Used in NERC Reliability Standards: https://www.nerc.com/pa/Stand/Glossary%20of%20Terms/Glossary_of_Terms.pdf, updated March 8, 2023. 5 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
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(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.

The FRS is based on PacifiCorp operational data recorded from January 2018 through December 2019 for load, wind, solar, and Non-VERs. PacifiCorp’s primary analysis focuses on the actual variability of load, wind, solar, and Non-VERs during 2018-2019. 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 covers variations in load, wind, solar, and Non-VERs, while implicitly accounting for the diversity between the different classes. An explicit adjustment is also made to account for diversity benefits realized because of PacifiCorp’s participation in the
Energy Imbalance Market (EIM) operated by the California Independent System Operator
Corporation (CAISO). The methodology in the FRS is like that employed in PacifiCorp’s 2019 IRP but has been enhanced in two areas.6 First, the historical period evaluated in the study has been expanded to include two
years, rather than one, to capture a larger sample of system conditions. Second, the methodology
for extrapolating results for higher renewable resource penetration levels has been modified to better capture the diversity between growing wind and solar portfolios. 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 levels of wind, solar and load.
The regulation reserve requirement methodologies produced by the FRS are applied in production cost modeling to determine the cost of the reserve requirements associated with incremental wind and solar capacity. After a portfolio is selected, the regulation reserve requirements specific to that portfolio can be calculated and included in the study inputs, such that the production cost impact
of the requirements is incorporated in the reported results. As a result, this production cost impact is dependent on the wind and solar resources in the portfolio as well as the characteristics of the dispatchable resources in the portfolio that are available to provide regulation reserves.

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”). 6 2019 IRP Volume II, Appendix F (Flexible Reserve Study): https://www.pacificorp.com/content/dam/pcorp/documents/en/pacificorp/energy/integrated-resource-plan/2019_IRP_Volume_II_Appendices_A-L.pdf
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Overview
The primary analysis in the FRS is to estimate 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. 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 diversity 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. A comparison of the results of the current analysis and that from previous IRPs is shown in Table F.1 and Table F.2. Flexible resource costs are portfolio dependent and vary over time. For more details, please refer
to Figure F.11 – Incremental Wind and Solar Regulation Reserve Costs.
Table F.1 - Portfolio Regulation Reserve Requirements
Wind Capacity Solar Capacity
Stand-alone Regulation Requirement
Portfolio Diversity Credit
Regulation Requirement with Diversity
Case (MW) MW (MW) (%) (MW)
CY2017 (2019 FRS) 2,750 1,021 994 47% 531
2018-2019 (2021 FRS) 2,745 1,080 1,057 49% 540
Table F.2 - 2023 Flexible Resource Costs as Compared to 2021 Costs, $/MWh

2025-2042 2025-2042 2023-2040 2023-2040
$1.38 $1.59 $1.58 $1.32

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 NERC regional reliability standards. Operating reserve generally 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-3.7 Regulation reserve is capacity that
PacifiCorp holds available to ensure compliance with the NERC Control Performance Criteria in

7 NERC Standard BAL-002-WECC-3 – Contingency Reserve: https://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-002-WECC-3.pdf
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BAL-001-2.8 Frequency response reserve is capacity that PacifiCorp holds available to ensure
compliance with NERC standard BAL-003-2.9 Each type of operating reserve is further defined below.
Contingency Reserve
Purpose: 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.
Volume: NERC regional reliability standard BAL-002-WECC-3 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.
Duration: Except within 60 minutes of a qualifying contingency event, a BAA must maintain the required level of contingency reserve at all times. Generally, this means that up to 60 minutes of generation are required to provide contingency reserve, though successive outage events may result in contingency reserves being deployed for longer periods. To restore contingency reserves,
other resources must be deployed to replace any generating resources that experienced outages,
typically either market purchases or generation from resources with slower ramp rates. Ramp Rate: Only up capacity available within ten minutes can be counted as contingency reserve. This can include “spinning” resources that are online and immediately responsive to system
frequency deviations to maintain compliance with frequency response obligations under BAL-
003-1.1, as well as from “non-spinning” resources that do not respond immediately, though they must still be fully deployed in ten minutes.10
Regulation Reserve
Purpose: 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
(BAAL) for more than 30 consecutive clock-minutes…

8 NERC Standard BAL-001-2 – Real Power Balancing Control Performance: https://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-001-2.pdf 9 NERC Standard BAL-003-2 — Frequency Response and Frequency Bias Setting: https://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-003-2.pdf 10 While the minimum spinning reserve obligation previously contained within BAL-002-WECC-2a was retired due to redundancy with frequency response obligations under BAL-003-2, PacifiCorp’s 2023 IRP does not explicitly model the frequency response obligation and retains the spinning obligation to ensure a supply of rapidly responding resources is maintained.
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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 monthly, it does not require
a response to 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.
Volume: NERC standard BAL-001-2 does not specify a regulation reserve requirement based on a simple formula, but instead requires utilities to hold sufficient reserve to meet performance standards as discussed above. The FRS estimates the regulation reserve necessary to meet Requirement 2 by compensating for the combined deviations of the load, wind, solar and Non-
VERs on PacifiCorp’s system. These regulation reserve requirements are discussed in more detail
later in the study. Ramp Rate: 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. 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. Duration: PacifiCorp is required to submit balanced load and resource schedules as part of its
participation in EIM. PacifiCorp is also required to submit resources with up flexibility and down flexibility to cover uncertainty and expected ramps across the next hour. Because forecasts are submitted prior to the start of an hour, deviations can begin before an hour starts. As a result, a flexible resource might be called upon for the entire hour. To continue providing flexible capacity in the following hour, energy must be available in storage for that hour as well. The likelihood of
deploying for two hours or more for reliability compliance (as opposed to economics) is expected to be small.
Frequency Response Reserve
Purpose: NERC standard BAL-003-2 specifies that each BAA must arrest frequency deviations and support the interconnection when frequency drops below the scheduled level. When a frequency drop occurs because of an event, PacifiCorp will deploy resources that increase the net
interchange of its BAAs and the flow of generation to the rest of the interconnection.
Volume: 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 megawatt (MW)/0.1 Herts (Hz). 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 2022 frequency response obligation was 25.3
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MW/0.1Hz for PACW, and 63.5 MW/0.1Hz for PACE.11 PacifiCorp’s combined obligation
amounts to 88.8 MW for a frequency drop of 0.1 Hz, or 266.4 MW for a frequency drop of 0.3 Hz. The performance measurement for contingency reserve under the Disturbance Control Standard (BAL-002-3)12, allows for recovery to the lesser of zero or the ACE value prior to the contingency
event, so increasing ACE above zero during a frequency event reduces the additional deployment
needed if a contingency event occurs. Because contingency, regulation, and frequency events are all relatively infrequent, they are unlikely to occur simultaneously. Because the frequency response standard is based on median performance during a year, overlapping requirements that reduced PacifiCorp’s response during a limited number of frequency events would not impact compliance.

As a result, any available capacity not being used for generation is expected to contribute to meeting PacifiCorp’s frequency response obligation, up to the technical capability of each unit, including that designated as contingency or regulation reserves. 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 the frequency drop. As a result, while a few
resources could hold a large amount of contingency or regulation reserve, frequency response may need to be spread over a larger number of resources. Additionally, only resources that have active and tuned governor controls as well as outer loop control logic will respond properly to frequency events.
Ramp Rate: Frequency response performance is measured over a period of seconds, amounting to under a minute. Compliance is based on the average response over the course of an event. As a result, a resource that immediately provides its full frequency response capability will provide the greatest contribution. That same resource will contribute a smaller amount if it instead ramps up
to its full frequency response capability over the course of a minute or responds after a lag. Duration: Frequency response events are less than one minute in duration.
Black Start Requirements
Black start service is the ability of a generating unit to start without an outside electrical supply and is necessary to help ensure the reliable restoration of the grid following a blackout. At this
time, PACW grid restoration would occur in coordination with Bonneville Power Administration
black start resources. The Gadsby combustion turbine resources can support grid restoration in PACE. PacifiCorp has not identified any incremental needs for black start service during the IRP study period.
Ancillary Services Operational Distinctions
In actual operations, PacifiCorp identifies two types of flexible capacity as part of its participation in the EIM. The contingency reserve held on each resource is specifically identified and is not

11 NERC. BAL-003-2 Frequency Response Obligation Allocation and Minimum Frequency Bias Settings for Operating Year 2022. https://www.nerc.com/comm/OC/RS%20Landing%20Page%20DL/Frequency%20Response%20Standard%20Resources/BA_FRO_Allocations_for_OY2022-document(002).pdf 12 NERC Standard BAL-002-3 – Disturbance Control Standard – Contingency Reserve for Recovery from a Balancing Contingency Event: https://www.nerc.com/pa/Stand/Reliability Standards/BAL-002-3.pdf
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available for economic dispatch within the EIM. Any remaining flexible capacity on participating
resources that is not designated as contingency reserve can be economically dispatched in EIM based on its operating cost (i.e. bid) and system requirements and can contribute to meeting regulation reserve obligations. Because of this distinction, resources must either be designated as contingency reserve or as regulation reserve. Contingency events are relatively rare while
opportunities to deploy additional regulation reserve in EIM occur frequently. As a result,
PacifiCorp typically schedules its lowest-cost flexible resources to serve its load and blocks off capacity on its highest-cost flexible resources to meet its contingency obligations, subject to any ramping limitations at each resource. This leaves resources with moderate costs available for dispatch up by EIM, while lower-cost flexible resources remain available to be dispatched down
by EIM.
Regulation Reserve Data Inputs
Overview
This section describes the data used to determine PacifiCorp’s regulation reserve requirements. 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 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.13 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
five-minute intervals are used throughout the regulation reserve analysis.
EIM base schedule and deviation data for each wind, solar and Non-VER transaction point were downloaded using the SettleCore application, 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 its transmission customers pursuant to the provisions of
Attachment T to PacifiCorp’s Federal Energy Regulatory Commission (FERC) approved Open
13 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-40 is the base schedule time point used throughout this study.
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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 Hourly base schedules
- VER data
o Five-minute interval actual generation
o Hourly base schedules - Non-VER data
o Five-minute interval actual generation
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 most 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. Load data has not been adjusted for transmission and distribution losses.
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Wind and Solar Data
The wind and solar classes include 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.14 Wind and solar, in comparison to load, often have 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.”15 The data included in the FRS for the wind and solar classes include all wind and solar 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. In total, the FRS study period includes an average of 2,745 megawatts of wind and 1,080 megawatts of solar.
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.”16The 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. In total, the FRS includes 2,202 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 requirement is also zero. The allocation of regulation reserve requirements and diversity benefits is discussed in more detail later in the study.
14 Order No. 764 at P 281; Order No. 764-B at P 210. 15 Order No. 764 at P 20 (emphasis added). 16 Id. at P 92.
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Regulation Reserve Data Analysis and Adjustment
Overview
This section provides details on adjustments made to the data to align the ACE calculation with
actual operations, and address data issues.
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.1 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.1 - Base Schedule Ramping Adjustment

Data Corrections
The data extracted from PacifiCorp’s systems for, wind, solar and Non-VERs was sourced from
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CAISO settlement quality data. This data has already been verified for inconsistencies as part of
the settlement process and needs minimal cleaning as described below. Regarding five-minute interval load data from the PI Ranger system, intervals were excluded from the FRS results if any five-minute interval suffered from at least one of the data anomalies that are described further below:
Load:
• Telemetry spike/poor connection to meter
• Missing meter data
• Missing base schedules VERs:
• 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. Rapid spikes in load telemetry either up or down are unlikely to be the result of conditions which require deployment of regulation reserve, particularly when they are transient. 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. Such events are also likely to be 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 within a short period, were assumed to have been covered through contingency reserve
deployment or to reflect inaccurate load measurements. Because they do not reflect periods that require regulation reserve deployment, such intervals are excluded from the analysis. During the study period, in PACW 15 minutes’ worth of telemetry spikes were excluded while no telemetry spikes were observed in PACE. There were also 10 minutes’ worth of missing load meter data,
and 82 hours of missing load base schedules.
The available VER data includes wind curtailment events which affect metered output. When these curtailments occur, the CAISO sends data, by generator, indicating the magnitude of the curtailment. This data is layered on top of the actual meter data to develop a proxy for what the
metered output would have been if the generator were not curtailed. Regulation reserve
requirements are calculated based on the shortfall in actual output relative to base schedules. By adding back curtailed volumes to the actual metered output, the shortfall relative to base schedules is reduced, as is the regulation reserve requirement. This is reasonable since the curtailment is directed by the CAISO or the transmission system operator to help maintain reliable operation, so
it should not exacerbate the calculated need for regulation reserves.
After review of the data for each of the above anomaly types, and out of 210,216 five-minute intervals evaluated, approximately 1,000 five-minute intervals, or 0.5% of the data, was removed due to data errors. 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.
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By removing anomalies, the FRS sample is smaller but remains reflective of the range of
conditions PacifiCorp experiences, including the impact on regulation reserve requirements of weather events experienced during the study period.
Regulation Reserve Requirement Methodology
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-40.17

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 - 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; - Solar; - 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 and frequency response requirements are defined formulaically by their respective reliability standards. 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
17 See footnote 12 above for explanation of PacifiCorp’s use of the T-40 base schedule time point in the FRS.
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reserve, they are excluded from the determination of the regulation reserve requirements. Because
frequency response reserve can overlap with that held for contingency and regulation reserve requirements it is similarly excluded from the determination of regulation reserve requirements. 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.18 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 two 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…
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 had experience operating under the standard, even before it became effective on July 1, 2016.

The three key elements in BAL-001-2 are: (1) the length of time (or “interval”) used to measure compliance; (2) 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.
The first element is the length of time used to measure compliance. Compliance under BAL-001-2 is measured over rolling thirty-minute intervals, with 60 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 is in compliance, so only the minimum deviation in each rolling thirty-minute interval is considered in determining compliance. As a result, PacifiCorp does not need to hold regulation reserve for deviations with duration less than 30 minutes.
The second element is the number of intervals where deviations are allowed to be outside the limits set 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. The third element is the bandwidth of acceptable deviation before an interval is considered out of
compliance. Under BAL-001-2, the acceptable deviation for each BAA is dynamic, varying as a function of the frequency deviation for the entire interconnect. When interconnection frequency exceeds 60 Hz, the dynamic calculation does not require regulation resources to be deployed regardless of a BAA’s ACE. As interconnection frequency drops further below 60 Hz, a BAA’s permissible ACE shortfall is increasingly restrictive.
18 NERC Standard BAL-001-2, https://www.nerc.com/pa/Stand/Reliability%20Standards/BAL-001-2.pdf
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Planning Reliability Target: Loss of Load Probability When conducting resource planning, it is common to use a reliability target that assumes a specified loss of load probability (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.

The FRS assumes that a regulation reserve forecasting methodology that results in 0.50 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 illustrated below. 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 does not 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 F.2 below shows the probability of exceeding the allowed deviation during a five-minute interval for a given level of ACE shortfall. For instance, an 82 MW ACE shortfall in PACW has a
one percent chance of exceeding the Balancing Authority ACE Limit. WECC-wide frequency can
change rapidly and without notice, and this causes large changes in the Balancing Authority ACE 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
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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.19,20 This cap is reflected in Figure F.2. Figure F.2 - Probability of Exceeding Allowed Deviation
In 2018-2019, 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.
Regulation Reserve Forecast: Amount Held To calculate the amount of regulation reserve required to be held while being compliant with BAL-001-2 – using a LOLP of 0.5 hours per year or less – a quantile regression methodology was used. Quantile regression is a type of regression analysis. Whereas the typical method of ordinary least
19 “Regional Industry Initiatives Assessment.” NWPP MC Phase 3 Operations Integration Work Group. Dec. 31, 2014. Pg. 14. Available at: www.nwpp.org/documents/MC-Public/NWPP-MC-Phase-3-Regional-Industry-Initiatives-Assessment12-31-2014.pdf 20 “NERC Reliability-Based Control Field Trial Draft Report.” Western Electricity Coordinating Council. Mar. 25, 2015. Available at: www.wecc.biz/Reliability/RBC%20Field%20Trial%20Report%20Approved%203-25-2015.pdf
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 25 50 75 100 125 150 175 200 225
Pr
o
b
a
b
i
l
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y

o
f

E
x
c
e
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d
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A
l
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o
w
e
d

D
e
v
i
a
t
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(
%
)
ACE Shortfall (MW)
Exceedance Probability (PACW)Exceedance Probability (PACE)
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squares results in estimates of the conditional mean (50th percentile) of the response variable given
certain values of the predictor variables, quantile regression aims at estimating other specified percentiles of the response variable. Eight regressions were prepared, one for each class (load/wind/solar/non-VER) and area (PACE/PACW). Each regression uses the following variables:
• Response Variable: the error in each interval, in megawatts;
• Predictor Variable: the forecasted generation or load in each interval, expressed as a percentage of area capacity;
The forecasted generation or load in each interval used as the predictor variable contributes to the regression as a combination of linear, square, and higher order exponential effects. Specifically, the regression identifies coefficients that correspond to the following functions for each class:
Load Error: Load Forecast1 + Constant
Wind Error: Wind Forecast2 + Wind Forecast1
Solar Error: Solar Forecast4 + Solar Forecast3 + Solar Forecast2 + Solar Forecast1
Non-VER Error: Non-VER Forecast2 + Non-VER Forecast1

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. 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 is adjusted to achieve a cumulative LOLP that corresponds to the annual reliability target.
Regulation Reserve Forecast
Overview The following forecasts are polynomial functions that cover a targeted percentile of all historical deviations. These forecasts are stand-alone forecasts, based on the difference between hour-ahead
base schedules and actual meter data, expressing the errors as a function of the level of forecast.
The stand-alone reserve requirement shown achieves the annual reliability target of 0.5 hours per year, after accounting for the dynamic Balancing Authority ACE Limit. The combined diversity error system requirements are discussed later in the study. Figure F.3- Figure F.8 illustrate the relationship between the regulation reserve requirements during 2018-2019 and the forecasted
level of output, for each resource class and control area. Both the regulation reserve requirements
and the forecasted level of output are expressed as a percentage of resource nameplate (i.e., as a capacity factor). Figure F.9 and Figure F.10 illustrate the same relationship between the regulation reserve requirements during 2018-2019 and the forecasted load for each control area. Both the regulation reserve requirements and the forecasted load are expressed as a percentage of the annual
peak load (i.e., as a load factor).

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Figure F.3 - Wind Regulation Reserve Requirements by Forecast - PACE
Figure F.4 - Wind Regulation Reserve Requirements by Forecast Capacity Factor - PACW

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Figure F.5 - Solar Regulation Reserve Requirements by Forecast Capacity Factor - PACE
Figure F.6 - Solar Regulation Reserve Requirements by Forecast Capacity Factor - PACW

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Figure F.7 – Non-VER Regulation Reserve Requirements by Capacity Factor - PACE
Figure F.8 – Non-VER Regulation Reserve Requirements by Capacity Factor - PACW

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Figure F.9 – Stand-alone Load Regulation Reserve Requirements - PACE
Figure F.10 – Stand-alone Load Regulation Reserve Requirements - PACW

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The results of the analysis are shown in Table F.3 below.
Table F.3 – Summary of Stand-alone Regulation Reserve Requirements

Non-VER 106 1,304 8.2%
Load 334 10,094 3.3%
VER - Wind 457 2,745 16.7%
VER - Solar 159 1,080 14.8%
Total 1,057

Portfolio Diversity and EIM Diversity Benefits
The EIM is a voluntary energy imbalance market service through the CAISO where market systems automatically balance supply and demand for electricity every fifteen and five minutes, dispatching least-cost resources every five minutes.
PacifiCorp and CAISO began full EIM operation on November 1, 2014. Several additional
participants have since joined the EIM, and more participants are scheduled to join in the next several 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. The EIM also has direct effects related to regulation reserve requirements. First, because of EIM participation, PacifiCorp has improved data used in the analysis contained in this FRS. The data
and control provided by the EIM allow PacifiCorp to achieve the portfolio diversity benefits
described in the first part of this section. Second, the EIM’s intra-hour capabilities across the broader EIM footprint provide the opportunity to reduce the amount of regulation reserve necessary for PacifiCorp to hold, as further explained in the second part of this section.
Portfolio Diversity Benefit
The regulation reserve forecasts described above 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 Solar, Wind, Non-VERs, and Load. As a result, the regulation reserve forecast for the portfolio can be reduced while still meeting the reliability target. In the historical period, portfolio diversity from the interactions between the various classes results in a regulation reserve
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requirement that is 36% lower than the sum of the stand-alone requirements, or approximately 679
MW.
EIM Diversity 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 provides the opportunity to further reduce the amount of regulation reserve PacifiCorp
must hold.
By pooling variability in load and resource output, EIM entities reduce the quantity of reserve required to meet flexibility needs. The EIM also facilitates procurement of flexible ramping 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 BAA requirements. This difference is known as the “diversity benefit” in the EIM. This diversity benefit reflects offsetting variability and lower combined uncertainty. This flexibility reserve (uncertainty requirement) 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 diversity benefit by first calculating an uncertainty requirement for each individual EIM BAA and then by comparing the sum of those requirements to the uncertainty requirement for the entire EIM area. The latter amount is expected to be less than the
sum of the uncertainty 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 diversity 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 diversity benefit associated with EIM participation, as these are derived from the structure of the EIM rather than resources contributed by other participants.

Table F.4 below provides a numeric example of uncertainty requirements and application of the calculated diversity benefit.

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Table F.4 – EIM Diversity Benefit Application Example
=a+b+c+= e-f = g / e = c * h = c - i

CAISO req't. before
req't. before benefi
req't. before benefi
W req't. before
Total req't. before benefit
req't. after benefi
Total diversity benefit
Diversity benefit ratio
PACE benefit
PACE req't. after benefit
(MW) (MW) (MW) (MW) (MW) (MW) (MW) (MW) (MW) (MW)
1 550 110 165 100 925 583 342 37.00% 61 104
2 600 110 165 100 975 636 339 34.80% 57 108

While the diversity benefit is uncertain, that uncertainty is not significantly different from the
uncertainty in the Balancing Authority ACE Limit previously described. In the FRS, PacifiCorp has credited the regulation reserve forecast based on a historical distribution of calculated EIM diversity benefits. While this FRS considers regulation reserve requirements in 2018-2019, the CAISO identified an error in their calculation of uncertainty requirements in early 2018. CAISO’s
published uncertainty requirements and associated diversity benefits are now only valid for March
2018 forward. To capture these additional benefits for this analysis, PacifiCorp has applied the historical distribution of EIM diversity benefits from the 12 months beginning March 2018. In the historical study period, EIM diversity benefits used in the FRS would have reduced regulation reserve requirements by approximately 140 MW.

The inclusion of EIM diversity benefits in the FRS reduces the magnitude, and thus probability, of reserve shortfalls and, in doing so, reduces the overall regulation reserve requirement. This allows PacifiCorp’s forecasted requirements to be reduced. As shown in Table F.5 below, the resulting regulation reserve requirement is 540 MW, which is a 49 percent reduction (including
the portfolio diversity benefit) compared to the stand-alone requirement for each class. This portfolio regulation forecast is expected to achieve an LOLP of 0.5 hours per year.
Table F.5 – 2018-2019 Results with Portfolio Diversity and EIM Diversity Benefits

Stand-alone Regulation Stand-alone Portfolio Regulation Portfolio
Scenario (aMW) (%) (aMW) (%) (MW) Determinant
Non-VER 106 8.2% 55 4.2% 1,304 Nameplate
Load 334 3.3% 172 1.7% 10,094 12 CP
VER - Wind 457 16.7% 237 8.6% 2,745 Nameplate
VER - Solar 159 14.8% 76 7.1% 1,080 Nameplate
Total 1,057 540

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Fast-Ramping Reserve Requirements
As previously discussed, Requirement 1 of BAL-001-2 specifies that PacifiCorp’s 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. The Regulation Reserve Forecast described above is evaluating requirements for extreme
deviations that are at least 30 minutes in duration, for compliance with Requirement 2 of BAL-
001-2. In contrast, compliance with CPS1 requires reserve capability to compensate for most conditions over a minute-to-minute basis. These fast-ramping resources would be deployed frequently and would also contribute to compliance with Requirement 2 of BAL-001-2, so they are a subset of the Regulation Reserve Forecast described above.

To evaluate CPS1 requirements, PacifiCorp compared the net load change for each five-minute interval in the study period to the corresponding value for Requirement 2 compliance in that hour from the Regulation Reserve Forecast, after accounting for diversity (resulting in a 540 MW average requirement). Resources may deploy for Requirement 2 compliance over up to 30 minutes,
so the average requirement of 540 MW would require ramping capability of at least 18.0 MW per
minute (540 MW / 30 minutes). Because CPS1 is averaged and evaluated monthly, 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. Resources capable of ensuring compliance in 95 percent of intervals are expected to
be sufficient to meet CPS1 and given that ACE may deviate in either a positive or negative direction, the 97.5th percentile of incremental requirements versus Requirement 2 in that interval was evaluated. At the 97.5th percentile, fast ramping requirements for PACE and PACW are 1.7 MW/minute and 0.8 MW/minute higher than the Requirement 2 ramp rate, respectively; however,
if dynamic transfers between the BAAs are available, the 97.5th percentile for system is 0.6 MW /
minute lower than the Requirement 2 value. When viewed on a system basis, this means that 30-minute ramping capability held for Requirement 2 would be sufficient to cover an adequate portion of the fast-ramping events to ensure CPS1 compliance.
Note that resources must respond immediately to ensure compliance with Requirement 1, as
performance is measured on a minute-to-minute basis. As a result, resources that respond after a delay, such as quick-start gas plants or certain interruptible loads, would not be suitable for Requirement 1 compliance, so these resources cannot be allocated the entire regulation reserve requirement. However, because Requirement 1 compliance is a small portion of the total regulation reserve requirement, these restrictions on resource type are unlikely to be a meaningful constraint.
In addition, CPS1 compliance is weighted toward performance during conditions when interconnection frequency deviations are large. The largest frequency deviations would also result in deployment of frequency response reserves, which are somewhat larger in magnitude, though
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they have a less stringent performance metric under BAL-003-2, based on median response during
the largest events. In light of the overlaps with BAL-001-2 Requirement 2 and BAL-003-2 described above, CPS1 compliance is not expected to result in an additional requirement beyond what is necessary to
comply with those standards.
Portfolio Regulation Reserve Requirements
The IRP portfolio optimization process contemplates the addition of new wind and solar capacity as part of its selection of future resources, as well as changes in peak load due to load growth and energy efficiency measure selection. These load and resource changes are expected to drive changes in PacifiCorp’s regulation reserve requirements that will vary from portfolio to portfolio.

The locations that have been identified as likely sites for future wind and solar additions are in relatively close proximity to existing wind and solar resources, and PacifiCorp’s portfolio of resources is already relatively diverse with significant wind in Wyoming, along the Columbia
River gorge, and in eastern Idaho/western Wyoming and significant solar in southern Utah and
southern Oregon. Because future resources are likely to be added in relatively close proximity to these existing resources, they are not likely to change the diversity for that class of resources as a whole. Given the sizeable sample of existing wind and solar resources in PACE and PACW, maintaining the existing level of diversity as a class of resources doubles or quadruples is a more
likely outcome than the continuing improvements previously assumed in the 2019 FRS. With that
in mind, the incremental regulation reserve analysis for the 2021 FRS methodology assumes that wind, solar, and load deviations scale linearly with capacity increases from the actual data in the 2018-2019 historical period.
While diversity within each class is not expected to change significantly, there is the opportunity
for greater diversity among the wind, solar, and load requirements. These portfolio-related benefits are inherently tied to the portfolio, so it is appropriate that they vary with the portfolio. To that end, the 2021 FRS methodology calculates the portfolio diversity benefits specific to a wide variety of wind and solar capacity combinations, rather than relying upon the historical portfolio diversity
value.
As part of the portfolio diversity calculation, the analysis assumes that minimum EIM flexible reserve requirements and EIM diversity benefits scale with changes in portfolio capacity. EIM minimum flexible reserve requirements are tied to the uncertainty in PacifiCorp’s requirements,
which grow with changes portfolio capacity, so it would be impacted directly. EIM diversity
benefits reflect PacifiCorp’s share of stand-alone requirements relative to those of the rest of the BAA’s participating in EIM. All else being equal, increases in PacifiCorp’s portfolio capacity would result in a greater proportion of the EIM diversity benefits being allocated to PacifiCorp.
Portfolio diversity is driven by interplay among the deviations by wind, solar, and load, so it is not
a single number, but rather is dependent on the specific conditions. The 2021 FRS methodology incorporates two mechanisms to better account for these interactions. First, a portfolio diversity value is calculated specific to each hour of the day in each season. Second, rather than applying an equal percentage reduction to all hours, diversity benefits are assumed to be highest when stand-
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alone requirements are highest. For example, there is more opportunity for offsetting requirements
when load, wind, and solar all have significant stand-alone requirements. With that in mind, diversity is applied as an exponent to the incremental requirement more than the EIM minimum requirement. The result of this calculation is a diversity benefit which is highest for large reserve requirements, and which approaches zero as the requirement approaches the EIM minimum, as
illustrated in Table F.6.
Table F.6 – Portfolio Diversity Exponent Example
Incremental Requirement w/

Stand-alone Reserve Req. (MW)
EIM Floor (MW)
Stand-alone Incremental Req. (MW)
d = c ^ 75% e = c ^ 85% f = c ^ 95% g = 1 - (b + d)/a h = 1 - (b + e)/a i = 1 - (b + f)/a
a b c = a - b 75% 85% 95% 75% 85% 95%
200 200 0 0 0 0 0% 0% 0%
250 200 50 19 28 41 12% 9% 4%
300 200 100 32 50 79 23% 17% 7%
350 200 150 43 71 117 31% 23% 9%
400 200 200 53 90 153 37% 27% 12%
450 200 250 63 109 190 42% 31% 13%
500 200 300 72 128 226 46% 34% 15%
For each combination of wind and solar capacity, the hourly portfolio diversity exponents for each season are increased in a stepwise fashion until the risk of regulation reserve shortfalls during an interval is sufficiently low and the overall risk of regulation reserve shortfalls achieves the target
of 0.5 hours per year. The resulting portfolio diversity is maximized for a combination of wind
and solar as summarized in Table F.7 and Table F.8 for PacifiCorp East and PacifiCorp West, respectively.
Table F.7 – PacifiCorp East Diversity by Portfolio Composition
(% Reduction vs. Stand-alone Requirements)
Ea
s
t

W
i
n
d

C
a
p
a
c
i
t
y

17.2% 18.8% 20.6%
19.2% 21.5% 23.0% 25.5% 26.5%
22.9% 24.1% 25.6% 27.9% 28.5% 29.0%
26.0% 27.3% 29.2% 30.7% 30.7% 30.5% 29.5%
30.4% 31.6% 32.9% 33.8% 32.7% 32.8% 32.8%
35.0% 36.2% 38.5% 37.1% 37.6% 36.2% 33.9% 31.9%
48.0% 45.8% 43.1% 39.5% 35.8% 32.2% 29.4%
46.4% 40.3% 36.4% 33.0% 30.0% 27.3%

2018-2019 Actual Wind and Solar Capacity

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Table F.8 – PacifiCorp West Diversity by Portfolio Composition
(% Reduction vs. Stand-alone Requirements)
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C
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26.2% 26.7% 27.6% 32.1% 34.8% 38.1%
29.6% 30.6% 31.4% 36.2% 39.5% 42.7% 42.7%
33.8% 34.5% 36.3% 40.8% 45.2% 46.2% 43.9%
38.8% 41.6% 43.1% 47.6% 48.4% 47.7% 45.0% 44.3%
42.4% 42.9% 48.6% 49.3% 47.7% 46.2% 44.4%
41.7% 47.1% 49.8% 47.4% 45.0% 43.2%

2018-2019 Actual Wind and Solar Capacity
After portfolio selection is complete, regulation reserve requirements are calculated specific to a portfolio’s load, wind, and solar resources in each year. The hourly regulation reserve requirement varies as a function of annual peak load net of energy efficiency selections as well as total wind
and solar capacity. The regulation reserve requirement also varies based on the hourly load net of
energy efficiency and hourly wind and solar generation values. Diversity exponents specific to the wind and solar capacity in each year are applied by hour and season, by interpolating among the scenarios illustrated in Tables F.7 and F.8. For example, the diversity exponent for hour five in the spring for a PACW study with 1,000 MW of wind and 1,000 MW of solar would reflect a
weighting of diversity exponents in hour five in the spring from four scenarios. The highest
weighting would apply to the 789 MW wind/1,041 MW solar scenario, and successively lower weightings would apply to 1,509 MW wind/1,041 MW solar, 789 MW wind/321 MW solar, and 1,509 MW wind/321 MW solar, with the total weighting for all four scenarios summing to 100%.
Finally, an adjustment is made to account for the ability of resources that are combined with
storage to offset their own generation shortfalls beyond what is already captured by the model. For example, combined solar and storage resources can offset their own generation shortfalls, up to their interconnection limit. In actual operation, a reduction in solar generation would enable additional storage discharge. However, within the PLEXOS model, there are no intra-hour
variations in load or renewable resource output and thus no potential increase in storage discharge.
Note that combined storage can only be discharged when there is a generation shortfall at the adjacent resource, so it cannot cover all shortfalls across the system. For example, many solar resources do not have co-located storage, and their errors would continue to need to be met with incremental reserves. Nonetheless, combined solar and storage can cover a portion of their own
shortfalls, and that portion increases as more combined storage resources are added to the system.
This adjustment reduces the hourly regulation reserve requirement that is entered in the model.
Regulation Reserve Cost
The PLEXOS model reports marginal reserve prices on an hourly basis. So long as the change in reserve obligations or capability from what was input for a study is relatively small, this reserve
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price can provide a reasonable estimate of the impact of changes in reserves, without requiring
additional model runs. To estimate wind and solar integration costs for the 2023 IRP, PacifiCorp prepared a PLEXOS scenario that reflected the final regulation reserve requirements, consistent with the Company’s
existing wind and resources plus selections in the preferred portfolio. Hourly regulation reserve
prices were reported from this study. Wind Integration The wind reserve case uses the 2021 FRS methodology to recalculate the wind reserve
requirement for a portfolio with 5 MW more wind resources starting in the first-year proxy
resources are potentially available and extending to the end of the IRP study horizon (2025-2042). The change in resources is applied equally between PACE and PACW, and is allocated pro-rata among all wind resources in the area, such that the aggregate hourly capacity factor is not impacted by the change in capacity. The change in wind capacity
results in incremental regulation reserve requirements that average approximately 16% of
the nameplate capacity of the wind. Wind integration costs are calculated by multiplying the hourly change in reserve requirements (in MW) by the hourly regulation reserve price in each hour of the year, and then dividing that total by the incremental wind generation over the year.
Solar Integration The solar reserve case uses the 2021 FRS methodology to recalculate the solar reserve requirement for a portfolio with 5 MW more solar resources starting in the first-year proxy resources are potentially available and extending to the end of the IRP study horizon (2025-
2042). The reduction in resources is applied equally between PACE and PACW, and is allocated pro-rata among all solar resources in the area, such that the aggregate hourly capacity factor is not impacted by the change in capacity. The change in solar capacity results in incremental regulation reserve requirements that average approximately 10% of the nameplate capacity of the solar. Solar integration costs are calculated by multiplying
the hourly change in reserve requirements (in MW) by the hourly regulation reserve price in each hour of the year, and then dividing that total by the incremental solar generation over the year. The incremental regulation reserve cost results for wind and solar are shown in Figure F.11. The
comparable regulation reserve costs from the 2021 FRS are also shown. Integration costs are high in the near term, as market prices are currently high and flexible capacity is somewhat limited. Integration costs fall as energy storage resources are added to the portfolio, as they can provide free operating reserves while charging and in any hour in which they are not discharging and not fully depleted, which for a four-hour energy storage resource is most of the day.

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Figure F.11 – Incremental Wind and Solar Regulation Reserve Costs

Flexible Resource Needs Assessment
Overview
In its Order No. 12-013 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:
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 2023 through 2042, 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.
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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 the PLEXOS model. The regulating reserve requirements are part of the inputs to the PLEXOS 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 2023 IRP: 10-minute spinning reserve
requirements, 10-minute non-spinning reserve requirements, and 30-minute regulation reserve requirements. The average reserve requirements for PacifiCorp’s two balancing authority areas are shown in Table F.9 below.
Table F.9 - Reserve Requirements (Average MW)

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;

Spin Non-spin Regulation Spin Non-spin Regulation
(10-minute) (10-minute) (30-minute) (10-minute) (10-minute) (30-minute)
East Requirement West Requirement
Year
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• 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 its share of generation and capacity 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 combustion turbines, the amount of reserve can be close
to the differences between their nameplate capacities and their minimum generation levels. In contrast, both coal and gas-converted steam turbines have slower ramp rates, and may ramp from minimum to maximum over an hour or more. In the current IRP, PacifiCorp’s reserve needs are increasingly met by energy storage resources, including contracted resources and proxy resource selections in the preferred portfolio.
Table F.10 lists the annual reserve capability from resources in PacifiCorp’s East and West balancing authority areas.21 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.

21 Frequency response capability is a subset of the 10-minute capability shown. Battery resources are capable of responding with their maximum output during a frequency event and can provide an even greater response if they were charging at the start of an event. PacifiCorp has sufficient frequency response capability at present and by 2025 the battery capacity currently contracted or added in the preferred portfolio will exceed PacifiCorp’s current 266.4 MW frequency response obligation for a 0.3 Hz event. As a result, compliance with the frequency response obligation is not anticipated to require incremental supply.
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Table F.10 - Flexible Resource Supply Forecast (Average MW)

Figure F.12 and Figure F.13 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. Note that keeping minimum amounts in energy storage or bringing thermal plants online and/or reducing their generation while online
could increase the available response beyond that shown in the figures, and accounts for some of the increase in supply after 2030. In addition, PacifiCorp currently can transfer a portion of the operating reserves held in either of its balancing authority areas to help meet the requirements of its other balancing authority area, based on the reserve need and relative economics of the available supply.
East Supply West Supply East Supply West Supply
(10-Minute) (10-Minute) (30-Minute) (30-Minute)Year
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Figure F.12 - Comparison of Reserve Requirements and Resources, East Balancing Authority Area (MW)

Figure F.13 - 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
MW
MW
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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 by other utilities has expanded
significantly with more participants scheduled for entry through 2023. 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 uncertainty requirement for the entire EIM footprint can be less than the sum of individual BAAs’ requirements. This difference is known as the “diversity benefit” in the EIM. This diversity 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. As indicated in OPUC order 12-013, electric vehicle technologies may be able to meet flexible
resource needs. For the first time in the 2023 IRP, electric vehicle load control is one of the demand
response options available for selection. While electric vehicle load control was not one of the programs selected to the preferred portfolio, new demand response programs included in the preferred portfolio provide 275 average megawatts of operating reserves by 2030, and 860 average megawatts of operating reserves by 2042. While operating reserves supply is projected to be well
in excess of operating reserve requirements, the rising supply of zero-cost renewable resources
increases the value associated with shifting load within the day and seasonally, rather than just within the hour as contemplated in this appendix.
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APPENDIX G – PLANT WATER CONSUMPTION STUDY
The information provided in this appendix is for PacifiCorp owned plants. Total water consumption and generation includes all owners for jointly-owned facilities.

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Table G.1 – Plant Water Consumption with Acre-Feet per Year
Gadsby includes a mix of both Rankine steam units and Brayton peaking gas turbines.
1 acre-foot of water is equivalent to 325,851 Gallons or 43,560 Cubic Feet.

Plant Name
Zero
Discharge
Cooling
Media 2019 2020 2021 2022
4-year
Average 2019 2020 2021 2022
Gals/
MWH
GPM/
MW
68,040 61,675 66,531 62,551 64,699 44,759,976 42,115,971 45,237,567 43,210,219 481 8.0
Acre-Feet Per Year
TOTAL
Net MWhs Per Year
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Table G.2 – Plant Water Consumption by State (acre-feet)
Table G.3 – Plant Water Consumption by Fuel Type (acre-feet)

UTAH PLANTS
Plant Name 2016 2017 2018 2019 2020 2021 2022
Currant Creek 124 116 110 101 95 113 85
Gadsby 262 100 205 281 409 339 454
Hunter 14,225 15,383 14,751 15,808 15,103 16,326 13,426
Huntington 9,189 9,653 9,804 9,028 7,929 12,019 11,717
Lake Side 3,619 2,698 3,648 3,894 4,075 4,421 4,591
TOTAL 27,419 27,950 28,518 29,112 27,611 33,217 30,274
Percent of total water consumption = 45.4%
WYOMING PLANTS
Plant Name 2016 2017 2018 2019 2020 2021 2022
Dave Johnston 8,864 8,231 8,325 8,485 7,856 6,571 5,901
Jim Bridger 18,000 19,047 20,067 19,893 18,184 19,103 19,076
Naughton 6,896 6,927 9,916 10,195 7,622 7,236 6,929
Wyodak 329 332 319 292 336 333 324
TOTAL 34,090 34,537 38,627 38,865 33,998 33,243 32,230
Percent of total water consumption = 54.6%
COAL FIRED PLANTS
Plant Name 2016 2017 2018 2019 2020 2021 2022
Dave Johnston 8,864 8,231 8,325 8,485 7,856 6,571 5,901
Hunter 14,225 15,383 14,751 15,808 15,103 16,326 13,426
Huntington 9,189 9,653 9,804 9,028 10,423 10,643 10,240
Jim Bridger 18,000 19,047 20,067 19,893 18,184 19,103 19,076
Naughton 6,896 6,927 9,916 10,195 7,622 7,236 6,929
Wyodak 329 332 319 292 336 333 324
TOTAL 57,504 59,573 63,182 63,701 59,524 60,212 55,896
Percent of total water consumption = 93.3%
NATURAL GAS FIRED PLANTS
Plant Name 2016 2017 2018 2019 2020 2021 2022
Currant Creek 124 116 110 101 95 113 85
Chehalis 48 54 33 63 66 71 47
Gadsby 262 100 205 281 409 339 454
Lake Side 3,619 2,698 3,648 3,894 4,075 4,421 4,591
TOTAL 4,053 2,968 3,996 4,339 4,644 4,943 5,178
Percent of total water consumption = 6.7%
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Table G.4 – Plant Water Consumption for Plants Located in the Upper Colorado River Basin (acre-feet)

Plant Name 2016 2017 2018 2019 2020 2021 2022
Hunter 14,225 15,383 14,751 15,808 15,103 16,326 13,426
Huntington 9,189 9,653 9,804 9,028 7,929 12,019 11,717
Naughton 6,896 6,927 9,916 10,195 7,622 7,236 6,929
Jim Bridger 18,000 19,047 20,067 19,893 18,184 19,103 19,076
TOTAL 48,311 51,010 54,537 54,924 48,839 54,684 51,148
Percent of total water consumption = 80.8%
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APPENDIX H – STOCHASTIC PARAMETERS
Introduction
For the 2023 IRP, PacifiCorp updated and re-estimated the stochastic parameters provided in the 2021 IRP for use in the development of the 2023 IRP preferred portfolio.
Plexos, 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), Plexos 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 Plexos is a two-factor (short- and long-run) mean reverting model.
PacifiCorp used short-run stochastic parameters for this Integrated Resource Plan (IRP); long-run parameters were set to zero since Plexos 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 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.
Overview
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.

1 Mean reversion is assumed to be zero in the long run.
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.
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Volatility
The standard deviation3(𝜎) is a measure of how widely values are dispersed from the average
value:
𝜎 ∑𝑥 𝜇
𝑛 1
where 𝜇 is the average value of the observations {x1, x2,…,xn}, and n is the number of observations.
Volatility (𝜎) 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:
𝜎 𝜎√𝑇
Volatilities are typically quoted on an annual basis but can be specified for any desired time (𝑇). Suppose the annual volatility of load is two percent. This implies that the standard deviation of the range of possible loads a year from now is two percent, while the standard deviation four years
from now is four percent.
Mean Reversion
If volatility was 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.

3 "Standard Deviation" and "Variance" are standard statistical terms describing the spread of possible outcomes. The Variance equals the Standard Deviation squared.
PACIFICORP – 2023 IRP APPENDIX H – STOCHASTIC PARAMETERS
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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
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shock or deviation for a particular variable and the mean reversion rate describes how quickly the
variable moves back toward the long-run mean after experiencing a shock.
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 for 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.
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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 Definitions
Winte December, January, and February Spring March, April, and May Summer June, July, and Augus
Fall September, October, and Novembe
Data Development
Basic Data Set:
The natural gas price data was organized into a consistent dataset with one natural gas price for each gas delivery point reported for each delivery day. The data was 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 2018 to 2021 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, 2018-2021

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
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instance, gas prices are expected to be higher during winter or as we move toward winter. This
expectation is already included in the gas price forecast and should not be considered a shock, or random event. To capture only the random or uncertain portion of price movements, a price index is developed that takes into account the expected portion of price movements. Three categories of price expectations are calculated:

Seasonal Median: 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. To account for this possible difference in the level of gas prices, the median gas price for each season
and year is calculated. For example, Sumas prices in the winter of 2018 average
$2.68/MMBtu. Monthly Median: 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 median price is calculated. For example, February prices in Sumas are 91 percent of the winter median 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 and found to be insignificant (expected variation by weekday did not exceed three percent of the weekly average).
These three components – seasonal median, monthly shape, and weekly shape – combine to form an expected price for each day. For example, the expected price of gas in Sumas on February 1, 2018 was $2.21/MMBtu, the product of the seasonal median and the monthly shape factor
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝐺𝑎𝑠 𝑃𝑟𝑖𝑐𝑒 𝑆𝑒𝑎𝑠𝑜𝑛𝑎𝑙 𝑀𝑒𝑑𝑖𝑎𝑛.𝑃𝑟𝑖𝑐𝑒 ∗ 𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑆ℎ𝑎𝑝𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑡ℎ𝑒 𝑆𝑒𝑎𝑠𝑜𝑛
The following chart shows the comparison of the actual Sumas prices with the "expected" prices:
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Figure H.5 – Daily Gas Prices for SUMAS Basin with "expected" prices, 2018-2021
Dividing the actual gas prices by the expected prices forms a price index with a median of one.
This index, illustrated by the chart below, captures only the random component of price movements—the portion not explained by expected seasonal, monthly, and weekly shape.
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Figure H.6 – Gas Price Index for SUMAS Basin, 2018-2021

Parameter Estimation – Autoregressive Model
Uncertainty parameters are calculated for each variable by regressing the movement of each
region’s price index compared to the previous day's index. Step 1 - Calculate Log Deviation of Price Index Since gas prices are lognormally 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:
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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.

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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 yesterday experienced a 10 percent jump over the norm, today's expected price would be 4 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 similarly 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. Like 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 was organized into a consistent dataset with one price for each region reported for each delivery day, like gas prices. The data covers the 2018 through 2021 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). To have a consistent price definition, a composite price, calculated based on 16
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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 like 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 the latest available spread between COB and Mid-C markets. Similarly, Four
Corner prices are filled using Palo Verde prices.

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 median, monthly shape, and weekly shape. For instance, the expected price
for January 2, 2018, in the Four Corners region was $24.22/megawatt hours (MWh). This price incorporates the 2018 winter median price of $26.00/MWh times the monthly shape factor for January of 90 percent and the weekday index for Saturday of 98 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, 2018-2021

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.
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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, 2018-2021

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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, 2018, in Portland was 275 megawatts (MW). This load incorporates the 2018 winter average load of 245 MW times the monthly shape factor for January of 99 percent and the weekday
index for Saturday also of 93 percent. The following chart shows the Portland actual and expected
loads over the analysis period. Figure H.10 – Daily Average Load for Portland, 2018-2021

Load Uncertainty Parameters: Uncertainty parameters are calculated for each load region, like 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.

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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, median hydro generation is calculated and analyzed on a weekly, rather than daily, basis.
Generation is calculated as the median hourly generation across the 168 hours in a week. The
hydro analysis covers the 2017 through 2021 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, 2017, through January 7, 2017 in the Western Region was
467 MW. This generation incorporates the 2017 winter median generation of 515 MW times the monthly shape factor for January of 113 percent. The following chart shows the western hydro actual and expected generation over the analysis period.
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Figure H.11 – Weekly Average Hydro Generation in the West, 2017-2021

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.
Step 1 - Calculate Residual Errors Calculate the residual errors of the regression analysis for all the variables. The residual error
represents the random portion of the deviation not explained by mean reversion. It is calculated
for each period as the difference between the actual value and the value predicted by the linear regression equation:
𝐸𝑟𝑟𝑜𝑟 𝐴𝑐𝑡𝑢𝑎𝑙 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑆𝑙𝑜𝑝𝑒 ∗ 𝑃𝑟𝑒𝑣𝑖𝑜𝑢𝑠 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝐼𝑛𝑡𝑒𝑟𝑐𝑒𝑝𝑡
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All of the residual errors are compiled by delivery date.
Step 2 - Calculate Correlations Correlate the residual errors of each pair of variables:
𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑋,𝑌 ∑𝑥 𝑥. ∗ 𝑦 𝑦.
∑𝑥 𝑥.∗∑𝑦 𝑦.

There are a few things to note about the correlation calculations. First, correlation data must always be organized so that the same period is being compared for both variables. 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 are 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 Winter Correlations
Deviation events that impact one part of PacifiCorp’s system do not necessarily affect other parts of the system, due to its geographic diversity and transmission constraints. The correlation between these different deviations can be low if the deviations are caused by different drivers. An example from the winter season is the nine percent correlation between the Southeast Idaho load area, which
is driven by weather events in PacifiCorp’s PACE balancing area, and Hydro, which is predominantly driven by weather events in PacifiCorp’s PACW balancing area, the unit commitment stack and unplanned unit outages.
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Table H.7 - Short-term Spring Correlations
Similarly, the spring season shows a very low correlation of 14 percent between the Northern California and Wyoming loads, which are driven by different local weather deviations and
different customer types. Wyoming loads are mostly driven by large industrial customers, whose
loads are relatively flat across the year. Table H.8 - Short-term Summer Correlations

In the summer season, 13 percent correlation has been observed between the deviations of Kern-Opal gas prices and Palo Verde power prices. Palo Verde prices are driven by a resource mix of southwest nuclear operations and gas unit dispatch based off SoCal gas prices. The operations of gas storage facilities and physical planned and unplanned maintenance of Kern-Opal and SoCal
pipelines are independent of each other.

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Table H.9 - Short-term Fall Correlations

In the fall, a low correlation of 11 percent has been observed between Mid-C market price
deviations and Wyoming load deviations. Market deviations are due to deviations in northwest weather patterns and resource mix while Wyoming loads are mostly dictated by planned or unplanned outages of industrial customer class.

APPENDIX I – CAPACITY EXPANSION RESULTS

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Table 9.1 – Non-Emitting Peaking (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - - - - - - - - 303 - - - - 1,240 - - - - -
P‐MN - - - - - - - - - - - 303 578 345 - - - - -
P‐MM - - - - - - - 606 - - - - - 345 289 - - - - -
P‐HH - - - - - - - - - - - - - - 951 - - - - -
P‐SC - - - - - - - - - 606 - - - - 634 - - - - -
P01‐JB3‐4 GC - - - - - - - 606 - - - - - 345 289 - - - - -
P02‐JB3‐4 EOL - - - - - - - 606 - - - - - 345 289 - - - - -
P03‐Hunter3‐SCR - - - - - - - 606 - - - - - 345 289 - - - - -
P04‐Huntington RET28 - - - - - - - 606 - - - - - 345 289 - - - - -
P05‐No NUC - - - - - - - 895 - 303 303 - - 345 289 - - - - -
P06‐No Forward Tech - - - - - - - 606 - - - - - 345 289 - - - - -
P07‐D3‐D2 32 - - - - - - - 606 - - - - - 345 289 - - - - -
P08‐No D3‐D2 - - - - - - - 606 - - - - - 345 289 - - - - -
P09‐No WY OTR - - - - - - - 606 - - - - - 345 289 - - - - -
P10‐Offshore Wind - - - - - - - 606 - - - - - - 289 - - - - -
P11‐Max NG - - - - - - - - - - - - - - - - - - - -
P12‐RET Coal 30 NG 40 - - - - - - - 606 - - - - - 345 1,790 - - - - -
P13‐All EE - - - - - - - 606 - - - - - 345 289 - - - - -
P14‐All GW - - - - - - - 606 - - - - - 345 289 - - - - -
P15‐No GWS - - - - - - - 606 - - - - - 345 289 - - - - -
P16‐No B2H - - - - - - - 606 - - - - - 345 289 - - - - -
P17‐Col3‐4 RET25 - - - - - - - 606 - - - - - 345 289 - - - - -
P18‐Cluster East - - - - - - - 606 - - - - - 345 289 - - - - -
P19‐Cluster West - - - - - - - 606 - - - - - 345 289 - - - - -
P20‐JB3‐4 CCUS - - - - - - - 606 - - - - - 345 289 - - - - -
Study

Table 9.2 - DSM Energy Efficiency (Installed Capacity MW)

Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN 123 220 259 197 216 219 240 258 637 103 160 170 161 281 586 163 170 165 139 412
P‐MN 123 220 259 198 217 221 243 259 637 105 160 170 161 288 586 164 170 165 139 412
P‐MM 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P‐HH 123 220 259 210 229 234 255 266 675 116 161 185 162 289 594 165 187 176 172 671
P‐SC 123 220 259 206 225 230 245 265 637 114 160 170 162 288 586 165 170 165 158 429
P01‐JB3‐4 GC 123 220 259 208 228 219 241 259 637 116 163 172 163 288 542 163 183 175 141 428
P02‐JB3‐4 EOL 123 220 259 208 228 219 240 258 637 115 161 171 161 288 542 163 184 176 141 428
P03‐Hunter3‐SCR 123 220 259 198 216 220 240 258 637 105 149 170 161 288 586 163 186 176 143 429
P04‐Huntington RET28 123 220 259 208 228 219 240 258 637 109 161 171 161 288 542 163 184 176 141 428
P05‐No NUC 123 220 259 208 228 219 240 260 638 106 161 171 161 288 542 163 184 176 141 429
P06‐No Forward Tech 123 220 259 208 228 219 240 260 638 106 161 171 161 288 542 163 184 176 141 429
P07‐D3‐D2 32 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P08‐No D3‐D2 123 220 259 198 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P09‐No WY OTR 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P10‐Offshore Wind 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P11‐Max NG 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P12‐RET Coal 30 NG 40 123 954 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P13‐All EE 123 220 259 289 330 334 392 457 1,016 215 301 283 292 457 816 230 253 241 343 1,231
P14‐All GW 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P15‐No GWS 123 220 259 198 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P16‐No B2H 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P17‐Col3‐4 RET25 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P18‐Cluster East 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P19‐Cluster West 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
P20‐JB3‐4 CCUS 123 220 259 197 214 219 236 261 665 112 175 185 162 277 594 150 170 169 139 426
Study

Table 9.3 – DSM Demand Response (Installed Capacity MW)

Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN 72 39 143 38 161 120 33 16 33 - - - 51 - - 170 19 19 - -
P‐MN 72 39 152 99 126 94 27 13 35 - - - - - 1 228 19 19 - -
P‐MM 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P‐HH 72 39 154 119 117 81 26 - 37 5 13 12 26 - - 239 22 19 - -
P‐SC 72 39 154 107 123 75 27 - 46 - - - 3 - - 246 19 19 - -
P01‐JB3‐4 GC 72 220 193 6 83 61 41 10 8 - - - 117 - - 121 21 20 - -
P02‐JB3‐4 EOL 72 220 199 12 77 64 43 9 11 - - 2 108 - - 125 20 39 - -
P03‐Hunter3‐SCR 72 53 167 105 111 90 31 13 35 - - 2 - - - 225 19 38 - -
P04‐Huntington RET28 72 220 199 12 77 64 43 9 11 - - 2 108 - - 125 20 39 - -
P05‐No NUC 72 220 199 12 75 68 43 9 47 - - 2 76 - - 123 20 39 - -
P06‐No Forward Tech 72 220 199 12 75 68 43 9 47 - - 2 76 - - 123 20 39 - -
P07‐D3‐D2 32 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P08‐No D3‐D2 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P09‐No WY OTR 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P10‐Offshore Wind 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P11‐Max NG 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P12‐RET Coal 30 NG 40 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P13‐All EE 72 39 152 109 119 91 29 13 35 - 1 - 2 - 4 265 70 20 - 778
P14‐All GW 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P15‐No GWS 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P16‐No B2H 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P17‐Col3‐4 RET25 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P18‐Cluster East 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P19‐Cluster West 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
P20‐JB3‐4 CCUS 72 39 152 109 133 81 27 16 22 - - - 7 - - 233 19 19 - -
Study

Table 9.4 – Renewable Wind (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - 194 1,717 - - - 500 - 11 5,477 1,821 - - - - - - - - -
P‐MN - 194 1,717 - - - 500 - - 6,025 3,565 - 450 - - - - - - -
P‐MM - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P‐HH - 194 1,717 - - 174 500 - - 7,922 2,321 - - - - - - - - -
P‐SC - 194 1,717 - - 457 500 - - 6,486 3,607 - - - - - - - - -
P01‐JB3‐4 GC - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P02‐JB3‐4 EOL - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P03‐Hunter3‐SCR - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P04‐Huntington RET28 - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P05‐No NUC - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P06‐No Forward Tech - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P07‐D3‐D2 32 - 194 1,937 - 100 300 - - - 6,165 1,755 - - - - - - - - -
P08‐No D3‐D2 - 194 1,937 - 100 300 - - - 2,349 1,282 - - - - - - - - -
P09‐No WY OTR - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P10‐Offshore Wind - 194 1,937 - 100 300 1,900 - - 2,683 1,459 - - - 540 - - - - -
P11‐Max NG - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P12‐RET Coal 30 NG 40 - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 676 - - - - -
P13‐All EE - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P14‐All GW - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P15‐No GWS - 194 296 - 100 300 - - - 2,349 1,282 - - - - - - - - -
P16‐No B2H - 194 1,937 - 100 - 1,900 400 - 2,783 959 - - - 540 - - - - -
P17‐Col3‐4 RET25 - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P18‐Cluster East - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P19‐Cluster West - 194 1,937 - 100 300 1,900 - - 2,783 1,359 - - - 540 - - - - -
P20‐JB3‐4 CCUS - 194 1,937 - 100 300 1,900 - - 2,733 1,359 - - - 540 - - - - -
Study

Table 9.5 – Renewable Solar (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - 1,469 1,600 - 2,519 1,298 - 288 241 - - - - 1,400 - - - - -
P‐MN - - 1,469 1,600 - 2,470 1,298 - 254 941 - - - - 600 - - - - -
P‐MM - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P‐HH - - 1,469 1,600 - 3,006 1,298 - 4 1,288 241 - - - - - - - - -
P‐SC - - 1,469 1,600 - 2,589 1,298 - 108 600 - 841 - - - - - - - -
P01‐JB3‐4 GC - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P02‐JB3‐4 EOL - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P03‐Hunter3‐SCR - - 1,469 2,524 483 1,832 200 - - 972 - 300 - - - - - - - -
P04‐Huntington RET28 - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P05‐No NUC - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P06‐No Forward Tech - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - 600 - - - - -
P07‐D3‐D2 32 - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P08‐No D3‐D2 - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P09‐No WY OTR - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P10‐Offshore Wind - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P11‐Max NG - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P12‐RET Coal 30 NG 40 - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P13‐All EE - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P14‐All GW - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P15‐No GWS - - 1,469 2,224 483 2,307 600 - 200 972 - 300 - - - - - - - -
P16‐No B2H - - 1,469 2,524 483 1,507 600 - - 972 600 300 - - - - - - - -
P17‐Col3‐4 RET25 - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
P18‐Cluster East - - 1,469 2,524 483 1,907 2,373 - - 972 - 300 - - - - - - - -
P19‐Cluster West - - 1,469 2,524 483 2,406 200 - - 972 - 300 - - - - - - - -
P20‐JB3‐4 CCUS - - 1,469 2,524 483 1,907 200 - - 972 - 300 - - - - - - - -
Study

Table 9.6 – Battery Storage (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - 954 1,600 160 2,008 1,647 - - - 400 - - - 2,560 - - - - -
P‐MN - - 954 1,600 - 2,304 1,647 - - 600 - - - - 2,356 - - - - -
P‐MM - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P‐HH - - 954 1,600 - 2,599 1,647 - - 600 - - - - 1,541 - - - - -
P‐SC - - 954 1,600 - 1,979 1,647 - - 600 - - - - 1,207 - - - - -
P01‐JB3‐4 GC - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P02‐JB3‐4 EOL - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P03‐Hunter3‐SCR - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P04‐Huntington RET28 - - 954 2,929 628 2,300 1,149 - - - - - - - 100 - - - - -
P05‐No NUC - - 954 2,929 628 1,900 1,149 - - 200 350 - - - 200 - - - - -
P06‐No Forward Tech - - 954 2,929 628 1,900 1,149 - - 200 350 - - - 200 - - - - -
P07‐D3‐D2 32 - - 754 2,929 824 1,900 1,149 - - - 150 - - - 200 - - - - (196)
P08‐No D3‐D2 - - 954 2,929 628 1,900 1,149 - - 800 150 - - - 200 - - - - -
P09‐No WY OTR - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P10‐Offshore Wind - - 954 2,929 628 1,900 1,149 - - - 150 - - - 500 - - - - -
P11‐Max NG - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P12‐RET Coal 30 NG 40 - - 754 2,929 824 1,900 1,149 - - - 150 - - - 1,323 - - - - (196)
P13‐All EE - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P14‐All GW - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P15‐No GWS - - 954 2,629 628 2,500 1,349 - - 800 150 - - - 200 - - - - -
P16‐No B2H - - 954 2,929 1,352 1,900 1,149 - - - 750 - - - 200 - - - - -
P17‐Col3‐4 RET25 - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
P18‐Cluster East - - 954 2,929 628 1,900 3,322 - - - 150 - - - 200 - - - - -
P19‐Cluster West - - 954 2,929 628 2,399 1,149 - - - 150 - - - 200 - - - - -
P20‐JB3‐4 CCUS - - 954 2,929 628 1,900 1,149 - - - 150 - - - 200 - - - - -
Study

Table 9.7 – Battery, Long Duration (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - - - - 600 - - - - - - - - 200 - - - - -
P‐MN - - - - - 400 - - - - - - - - - - - - - -
P‐MM - - - - - - - - - - 150 - - - 200 - - - - -
P‐HH - - - - - 600 - - - - - - - - 200 - - - - -
P‐SC - - - - - 400 - - - - - - - - 784 - - - - -
P01‐JB3‐4 GC - - - - - - - - - - 150 - - - 200 - - - - -
P02‐JB3‐4 EOL - - - - - - - - - - 150 - - - 200 - - - - -
P03‐Hunter3‐SCR - - - - - - - - - - 150 - - - 200 - - - - -
P04‐Huntington RET28 - - - - - - - - - - - - - - 200 - - - - -
P05‐No NUC - - - - - - - - - - 150 - - - 200 - - - - -
P06‐No Forward Tech - - - - - - - - - 300 450 - - - 200 - - - - -
P07‐D3‐D2 32 - - 600 - - - - - - - 150 - (600) - 200 - - - - -
P08‐No D3‐D2 - - - - - - - - - 600 150 - - - 200 - - - - -
P09‐No WY OTR - - - - - - - - - - 150 - - - 200 - - - - -
P10‐Offshore Wind - - - - - - - - - - 150 - - - 200 - - - - -
P11‐Max NG - - - - - - - - - - 150 - - - 200 - - - - -
P12‐RET Coal 30 NG 40 - - - - - - - - - - 150 - - - 200 - - - - -
P13‐All EE - - - - - - - - - - 150 - - - 200 - - - - -
P14‐All GW - - - - - - - - - - 150 - - - 200 - - - - -
P15‐No GWS - - - - - - - - - 600 150 - - - 200 - - - - -
P16‐No B2H - - - - - - - - - - 150 - - - 200 - - - - -
P17‐Col3‐4 RET25 - - - - - - - - - - 150 - - - 200 - - - - -
P18‐Cluster East - - - - - - - - - - 150 - - - 200 - - - - -
P19‐Cluster West - - - - - - - - - - 150 - - - 200 - - - - -
P20‐JB3‐4 CCUS - - - - - - - - - - 150 - - - 200 - - - - -
Study

Table 9.8 – Nuclear (Installed Capacity MW)1
1 – Positive values indicate installed capacity in the first full year of operations
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - - - - - - 500 - 1,000 - - - - - - - - - -
P‐MN - - - - - - - 500 - 1,000 - - - - - - - - - -
P‐MM - - - - - - - 500 - 500 500 - - - - - - - - -
P‐HH - - - - - - - 500 - 1,000 - - - - 500 - - - - -
P‐SC - - - - - - - 500 - - 500 500 - - - - - - - -
P01‐JB3‐4 GC - - - - - - - 500 - 500 500 - - - - - - - - -
P02‐JB3‐4 EOL - - - - - - - 500 - 500 500 - - - - - - - - -
P03‐Hunter3‐SCR - - - - - - - 500 - 500 500 - - - - - - - - -
P04‐Huntington RET28 - - - - - - - 500 - 500 500 - - - - - - - - -
P05‐No NUC - - - - - - - - - - - - - - - - - - - -
P06‐No Forward Tech - - - - - - - - - - - - - - - - - - - -
P07‐D3‐D2 32 - - - - - - - 500 - 500 500 - - - - - - - - -
P08‐No D3‐D2 - - - - - - - 500 - 500 500 - - - 1,000 - - - - -
P09‐No WY OTR - - - - - - - 500 - 500 500 - - - - - - - - -
P10‐Offshore Wind - - - - - - - 500 - 500 500 - - - - - - - - -
P11‐Max NG - - - - - - - - - - - - - - - - - - - -
P12‐RET Coal 30 NG 40 - - - - - - - 500 - - - - - - - - - - - -
P13‐All EE - - - - - - - 500 - 500 500 - - - - - - - - -
P14‐All GW - - - - - - - 500 - 500 500 - - - - - - - - -
P15‐No GWS - - - - - - - 500 - 500 500 - - - 1,000 - - - - -
P16‐No B2H - - - - - - - 500 - 500 500 - - - - - - - - -
P17‐Col3‐4 RET25 - - - - - - - 500 - 500 500 - - - - - - - - -
P18‐Cluster East - - - - - - - 500 - 500 500 - - - - - - - - -
P19‐Cluster West - - - - - - - 500 - 500 500 - - - - - - - - -
P20‐JB3‐4 CCUS - - - - - - - 500 - 500 500 - - - - - - - - -
Study

Table 9.9 – Coal End-of-life Retirements1
1 – Negative values indicate retirement of coal fueled capacity
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - - (82) - (253) (328) (148) - - - - - - - - - - - -
P‐MN - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P‐MM - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P‐HH - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P‐SC - - - (82) - (253) (328) (148) - (699) - - - - - - - (330) - -
P01‐JB3‐4 GC - - - (82) - (253) (328) (148) - - - - - - - (699) - (330) - -
P02‐JB3‐4 EOL - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P03‐Hunter3‐SCR - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P04‐Huntington RET28 - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P05‐No NUC - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P06‐No Forward Tech - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P07‐D3‐D2 32 - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P08‐No D3‐D2 - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P09‐No WY OTR - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P10‐Offshore Wind - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P11‐Max NG - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P12‐RET Coal 30 NG 40 - - - (82) - (253) (328) (148) - - - - - - - - - - - -
P13‐All EE - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P14‐All GW - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P15‐No GWS - - - (82) - (253) (328) (148) - - - - - - (330) - - - - -
P16‐No B2H - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P17‐Col3‐4 RET25 - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P18‐Cluster East - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P19‐Cluster West - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
P20‐JB3‐4 CCUS - - - (82) - (253) (328) (148) - - - - - - - - - (330) - -
Study

Table 9.10 – Coal with SNCR Installation1,2
1 – Positive values indicate first full year of operations with SNCR installed 2 – Negative values indicate retirement of coal fueled capacity with SNCR
Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - - - 2,067 - - - - - (2,067) - - - - - - - - - -
P‐MN - - - 2,335 - - - - - (2,067) - - - - - - - (268) - -
P‐MM - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P‐HH - - - 2,335 - - - - - (2,067) - - - - - - - (268) - -
P‐SC - - - 2,335 - - - - - (2,067) - - - - - - - (268) - -
P01‐JB3‐4 GC - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P02‐JB3‐4 EOL - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P03‐Hunter3‐SCR - - - 1,864 - - - - - (418) (1,178) - - - - - - (268) - -
P04‐Huntington RET28 - - - 2,335 - (459) - - - (418) (1,190) - - - - - - (268) - -
P05‐No NUC - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P06‐No Forward Tech - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P07‐D3‐D2 32 - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P08‐No D3‐D2 - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P09‐No WY OTR - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P10‐Offshore Wind - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P11‐Max NG - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P12‐RET Coal 30 NG 40 - - - 2,067 (450) - - - - (418) (1,199) - - - - - - - - -
P13‐All EE - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P14‐All GW - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P15‐No GWS - - - 2,335 - - - - - (418) (1,649) - - - (268) - - - - -
P16‐No B2H - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P17‐Col3‐4 RET25 - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P18‐Cluster East - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P19‐Cluster West - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
P20‐JB3‐4 CCUS - - - 2,335 - - - - - (418) (1,649) - - - - - - (268) - -
Study
213

Table 9.11 – Coal to Natural Gas Conversions1,2
1 – Positive values indicate first full year of natural gas-fueled operation 2 – Negative values indicate retirement of gas-converted capacity

Installed Capacity, MW
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
P-LN - 713 - 370 598 - - 699 - (330) - - - - (370) (1,413) - (268) - -
P‐MN - 713 - 370 - - - 340 (354) - - - - (160) (210) (699) - - - -
P‐MM - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P‐HH - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P‐SC - 713 - 370 - - - - - - - - - - (370) (713) - - - -
P01‐JB3‐4 GC - 713 - 370 - - - - - - - - - - (370) (713) - - - -
P02‐JB3‐4 EOL - 713 - 1,069 - - - - - - - - - - (370) (1,413) - - - -
P03‐Hunter3‐SCR - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P04‐Huntington RET28 - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P05‐No NUC - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P06‐No Forward Tech - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P07‐D3‐D2 32 - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P08‐No D3‐D2 - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P09‐No WY OTR - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P10‐Offshore Wind - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P11‐Max NG - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P12‐RET Coal 30 NG 40 - 713 - 370 598 - - 699 - - - - - - (370) (1,413) - (598) - -
P13‐All EE - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P14‐All GW - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P15‐No GWS - 713 - 370 - - - 699 - - - - - - (1,783) - - - - -
P16‐No B2H - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P17‐Col3‐4 RET25 - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P18‐Cluster East - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P19‐Cluster West - 713 - 370 - - - 699 - - - - - - (370) (1,413) - - - -
P20‐JB3‐4 CCUS - 713 - 370 - - - 349 - - - - - - (370) (1,062) - - - -
Study
214
PACIFICORP - 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

217

APPENDIX J – STOCHASTIC SIMULATION RESULTS
The following figures provide the cost summary detail comparing the MT model 95th percentile
results to the mean results. This can indicate which cost categories pose the largest risks. Note that the 95th percentile sample is determined from the present value impact over the entire IRP study horizon, so it is not the illustrating the range of risk in each individual year.
2023 IRP Preferred Portfolio

(P01) Jim Bridger 3 & 4 GC 2026

($10)
($5)
$0
$5
$10
$15
$20
$25
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$62 
($20)
($10)
$0
$10
$20
$30
$40
$50
$60
$70
Net Difference In Total System Cost
Net Cost/(Benefit)Cumulative PVRR(d)
($10)
($5)
$0
$5
$10
$15
$20
$25
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$66 
($20)
($10)
$0
$10
$20
$30
$40
$50
$60
$70
$80
Net Difference In Total System Cost
Net Cost/(Benefit)Cumulative PVRR(d)
215
PACIFICORP – 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

216

(P02) Jim Bridger 3 & 4 Coal EOL

(P03) Hunter 3 SCR
(P04) Retire Huntington 2028

($5)
$0
$5
$10
$15
$20
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$50 
($20)
($10)
$0
$10
$20
$30
$40
$50
$60
Net Difference In Total System Cost
Net Cost/(Benefit)Cumulative PVRR(d)
($10)
($5)
$0
$5
$10
$15
$20
$25
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$59 
($20)
($10)
$0
$10
$20
$30
$40
$50
$60
$70
Net Difference In Total System Cost
Net Cost/(Benefit)Cumulative PVRR(d)
($10)
($5)
$0
$5
$10
$15
$20
$25
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$63 
($20)
($10)
$0
$10
$20
$30
$40
$50
$60
$70
Net Difference In Total System Cost
Net Cost/(Benefit)Cumulative PVRR(d)
PACIFICORP - 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

217
(P05) No NUC add Peaker

(P06) No NUC No Forward Tech

(P07) D3 and D2 in 2032

($5)
$0
$5
$10
$15
$20
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
20
3
8
20
3
9
20
4
0
20
4
1
20
4
2
Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$52 
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Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$52 
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0
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1
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Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$36 
($20)
($10)
$0
$10
$20
$30
$40
$50
Net Difference In Total System Cost
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PACIFICORP – 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

216
(P08) No D3 and D2

(P09) WY No OTR

(P-10) Offshore Wind

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Annual Change in Cost by Line Item
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Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$35 
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$0
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$15
$20
$25
$30
$35
$40
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PACIFICORP - 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

217
(P-11) Max Nat Gas ( No NuC Peaker)

(P12) Coal Retire end 2029 Gas end of 2039

(P13) - ALL EE

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Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$48 
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($10)
$0
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PACIFICORP – 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

216
(P14) All Gateway

(P15) No GWS

(P16) No B2H

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Annual Change in Cost by Line Item
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$62 
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Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
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PACIFICORP - 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

217
(P18) Cluster East

(P19) Cluster West

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Annual Change in Cost by Line Item
Coal & Gas Variable Proxy Resource Costs Emissions Net Market Transactions
$35 
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PACIFICORP – 2023 IRP APPENDIX J – STOCHASTIC SIMULATION RESULTS

216

222
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION
APPENDIX K – CAPACITY CONTRIBUTION
Introduction
The capacity contribution of a resource is represented as a percentage of that resource’s nameplate
or maximum capacity and is a measure of the ability of a resource to reliably meet demand. This
capacity contribution affects PacifiCorp’s resource planning activities, which are intended to ensure there is sufficient capacity on its system to meet its load obligations inclusive of a planning reserve margin. Because of the increasing penetration of variable energy resources (such as wind and solar) and energy-limited resources (such as storage and demand response), planning for
coincident peak loads is no longer sufficient to determine the necessary amount and timing of new
resources. 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 load obligations and a planning reserve margin in all hours of each year. Because all resources provide both energy and capacity benefits, identifying the resource that can provide additional capacity at the lowest
incremental cost to customers is not straightforward. A resource’s energy value is dependent on
its generation profile and location, as well as the composition of resources and transmission in the overall portfolio. Similarly, a resource’s capacity value (or contribution to ensuring reliable system operation) is also dependent on both its characteristics and the composition of the overall portfolio. To further complicate the analysis, PacifiCorp’s portfolio composition changes
dramatically over time, as a result of retirements and [Grab your reader’s attention with a great
quote from the document or use this space to emphasize a key point. To place this text box anywhere on the page, just drag it.] expiring contracts.
In the 2019 IRP, PacifiCorp developed initial capacity contribution estimates for wind and solar capacity that accounted for expected declining contributions as the level of penetration increased. A key assumption in this analysis was that only a single variable was modified, for example, when evaluating solar penetration level, the capacity from wind and energy storage resources in the portfolio were held constant. As the preparation of the 2019 IRP continued, PacifiCorp identified
that these initial estimates did not adequately account for the interactions between solar, wind, and energy storage and thus did not ensure that each portfolio was adequately reliable. Therefore, as part of the 2019 IRP PacifiCorp assessed each portfolio to verify that it would support reliable operation in each hour of the year. PacifiCorp has continued to perform this portfolio-wide reliability assessment as part of the 2021 and 2023 IRPs.
PacifiCorp calculates the 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 CF Method calculates a capacity contribution based on a resource’s expected availability during periods when the risk of loss of
load events is highest, based on the loss of load probability (LOLP) in each hour. This CF Method analysis is performed using a portfolio that is comparable to the preferred portfolio. For the reasons discussed above, this analysis provides a reasonable estimate of capacity contribution value so long as the changes relative to the preferred portfolio are small, since in effect, the CF

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) at: www.nrel.gov/docs/fy12osti/54704.pdf
223
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION

Method calculates the marginal capacity contribution of a one megawatt resource addition. Changes to the locations and quantities of wind, solar, and energy storage are key drivers of the marginal capacity contribution results.
CF 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 a more computationally intensive reliability-based 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 a reliability-based metric. 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 to produce a capacity contribution value. The weighting factors based on LOLP are defined as:

𝑤𝐿𝑂𝐿𝑃
∑𝐿𝑂𝐿𝑃
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 𝑤𝐶,

where Ci is the capacity factor of the resource in hour i, and CV is the weighted capacity value of
the resource. For fixed profile resources, including wind, solar, and energy efficiency, the average LOLP values across all iterations are sufficient, as the output of these resources is the same in each iteration. To
determine the capacity contribution of fixed profile resources using the CF Method, PacifiCorp
implemented the following three steps: 1. A multi-iteration hourly Monte Carlo simulation of PacifiCorp’s system was produced using the Plexos Short-Term (ST) model. The key stochastic variables assessed as part of
this analysis are loads, thermal outages, and hydro conditions. The LOLP for each hour in the year is calculated by counting the number of iterations in which system load and/or reserve obligations could not be met with available resources and dividing by the total
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION
number of iterations.2 For example, if in hour 19 on December 22nd there are three iterations with shortfalls out of a total of 50 iterations, then the LOLP for that hour would be 6 percent.3
2. Weighting factors were determined based upon the LOLP in each hour divided by the sum
of LOLP among all hours within the same summer or winter season. In the example noted above, the sum of LOLP among all winter hours is 58 percent.4 The weighting factor for hour 19 on December 22nd would be 1.0417 percent.5 This means that 1.0417 percent of all winter loss of load events occurred in hour 19 on December 22nd and that a resource
delivering in only in that single hour would have a winter capacity contribution of 1.0417 percent. 3. The hourly weighting factors are then applied to the capacity factors of fixed profile 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 19 on December 22nd, its weighted winter capacity contribution for that hour would be 0.4271 percent.6 For resources which are energy limited, such as energy storage or demand response programs, the
LOLP values in each iteration must be examined independently, to ensure that the available storage
or control hours are sufficient. Continuing the example of December 22nd described above, consider if hour 18 and hour 19 both have three hours with energy or reserve shortfalls out of 500 iterations. If all six shortfall hours are in different iterations, a 1-hour energy storage resource could cover all six hours. However, if the six shortfall hours are in the same three iterations in hour 18
and hour 19 (i.e. 2-hour duration events), then a 1-hour storage resource could only cover three of
the six shortfall hours. Additional considerations are also necessary for hybrid resources which share an interconnection and cannot generate their maximum potential output simultaneously.
The details of the wind and solar resource modeling in the study period are an important aspect of
the results. The study includes specific wind and solar volumes by resource for each hour in the period and includes the effects of calm and cloudy days on resource output. Where data was available, the modeled generation profiles for proxy resources are derived from calendar year 2018 hourly generation profiles of existing resources, adjusted to align with the expected annual output
of each proxy resource.
The use of correlated hourly shapes produces variability across each month and a reasonable correlation between resources of the same type that are located in close proximity. It also results
2 While PacifiCorp participates in the Northwest Power Pool (NWPP) reserve sharing agreement, this only provides energy from other participants within the first hour of a contingency event, e.g. a forced outage of a generator or transmission line. Shortfalls in the 2023 IRP are much more likely to result from changes in load, renewable resource output, or energy storage limitations, which do not qualify as contingency events. In light of this, PacifiCorp’s analysis includes the first hour of every shortfall event. 3 0.6 percent = 3 / 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 288 winter ENS iteration-hours out of total of 5,832 winter hours. As a result, the sum of LOLP for the winter is 288 / 500 = 58 percent. There are 579 summer ENS iteration-hours out of total of 2,928 summer hours. As a result, the sum of LOLP for the summer is 579 / 500 = 116 percent. 5 1.0417 percent = 0.6 percent / 58 percent, or simply 1.0417 percent = 3 / 288. 6 0.4271 percent = 1.0417 percent x 41.0 percent.
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION

in days with higher generation and days with lower generation in each month. As one would expect, days with lower renewable generation are more likely to result in shortfall events. As a result, basing CF Method capacity contribution calculations on an average or 12-month by 24-hour forecast of renewable generation will tend to overstate capacity contribution, particularly if there
is a significant quantity of similarly located resources of the same type already in the portfolio, or
if an appreciable quantity of resource additions is being contemplated. Even if an hourly renewable generation forecast is used, capacity contributions can be overstated if the weather underlying the forecast is not consistent with that used for similarly located resources used to develop the CF Method results. Because similarly located resources of the same type would experience similar
weather in actual operations, a mismatch in the underlying weather conditions used in renewable generation forecasting will create diversity in the generation supply than would not occur in actual operations.
Because they are both influenced by weather, a relationship between renewable output and load is expected. To assess this relationship, PacifiCorp gathered information on daily wind and solar
output from 2016-2019 and compared it to the load data from that period, the same load data that
was used to determine stochastic parameters.
Each of the days in the historical period was assigned to a tier based on the rank of its daily average load within that month. This was done independently for the east and west sides of the system. The seven tiers were defined as follows:
Tier 1: The peak load day
Tier 2: 2nd – 5th highest load days
Tier 3: Days 6-10
Tier 4: Days 11-15
Tier 5: Days 16-20
Tier 6: Days 21-25
Tier 7: Days 26-31
The average wind and solar generation on the days in each tier was then compared to the average wind and solar generation for the entire month. The results indicated that west-side wind is often below average during the highest load days in a month, and above average during the lowest load
days in a month. The results for other resource types were less pronounced, but do exhibit some
patterns, as shown in Figure K.1 and Figure K.2.
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION
Figure K.1 – Renewable Resources vs. High Load Conditions

Figure K.2 – Renewable Resources vs. Low Load Conditions

Standard stochastic evaluation of prices, loads, etc. is based on standard deviations and mean reversion statistics. The results indicate that wind and solar output does exhibit relationships with
PACIFICORP – 2023 IRP APPENDIX K – CAPACITY CONTRIBUTION

load, but they are poorly represented by standard deviations – a different modeling technique is necessary.
Because of the complexity of the data, PacifiCorp did not attempt to develop wind and solar generation that varies by stochastic iteration for the 2023 IRP. Instead, PacifiCorp used a
technique using the existing input framework: a single 8760 profile for each wind and solar
resource that repeats every year. Because the load forecast rotates with the calendar, such that the peak load day moves to different calendar days, this creates differences in the alignment of load and renewable output across the IRP study horizon.
The order of the 2018 historical days was rearranged so that the forecasted intra-month variation
in renewable output was reasonably aligned with the intra-month variation observed in the
historical period for the days in the same load tier. Each day of renewable resource output derived from the 2018 history is mapped to a specific day for modeling purposes – only the order of the day’s changes. To maintain correlations within wind and solar output, all wind and solar resources across the entire system are mapped using the same days.
While this technique builds on previous modeling and produces a reasonable forecast that captures some of the relationships between wind, solar, and load, additional work is needed in future IRPs to explore the variation and diversity of solar and wind output and further relationships with load.

228
PACIFICORP – 2023 IRP APPENDIX L – PRIVATE GENERATION STUDY
229
APPENDIX L – PRIVATE GENERATION STUDY
Introduction
DNV prepared the Private Long-Term Resource Assessment for PacifiCorp. A key objective of this research is to assist PacifiCorp in developing private generation resource penetration forecasts
to support its 2023 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 under low, base and high penetration scenarios.

PACIFICORP – 2023 IRP APPENDIX L – PRIVATE GENERATION STUDY

230

DNV – www.dnv.com Page i

PRIVATE GENERATION FORECAST
Behind-The-Meter Resource
Assessment
PacifiCorp

Date: February 2, 2023

DNV – www.dnv.com Page ii

Table of Contents
1 EXECUTIVE SUMMARY.......................................................................................................................................... 8
1.1 Study Methodologies and Approaches ..................................................................................................................... 9
1.1.1 State-Level Forecast Approach .......................................................................................................................... 9
1.2 Private Generation Forecast .................................................................................................................................. 11
2 STUDY BACKGROUND ........................................................................................................................................ 14
3 STUDY APPROACH AND METHODS................................................................................................................... 16
3.1 Technology Attributes ............................................................................................................................................ 16
3.1.1 Solar PV ........................................................................................................................................................... 16
3.1.1.1 PV Only ....................................................................................................................................................... 17
3.1.1.2 PV + Battery ................................................................................................................................................ 18
3.1.2 Small-Scale Wind ............................................................................................................................................. 24
3.1.3 Small-Scale Hydropower .................................................................................................................................. 24
3.1.4 Reciprocating Engines ...................................................................................................................................... 25
3.1.5 Microturbines .................................................................................................................................................... 26
3.2 Customer Perspectives .......................................................................................................................................... 27
3.2.1 Customer Awareness ....................................................................................................................................... 28
3.2.2 Motivating Factors for Adoption ........................................................................................................................ 28
3.2.3 Barriers to Adoption .......................................................................................................................................... 28
3.2.4 Other Considerations ........................................................................................................................................ 28
3.2.5 Incentives Overview ......................................................................................................................................... 29
3.3 Current Private Generation Market .......................................................................................................................... 1
3.4 Forecast Methodology .............................................................................................................................................. 3
3.4.1 Economic Analysis ............................................................................................................................................. 3
3.4.2 Technical Feasibility ........................................................................................................................................... 5
3.4.3 Market Adoption ................................................................................................................................................. 6
4 RESULTS ................................................................................................................................................................. 9
4.1 Generation Capacity Results by State ................................................................................................................... 11
4.1.1 California .......................................................................................................................................................... 12
4.1.1.1 California PV Adoption by Sector ................................................................................................................ 15
4.1.2 Idaho ................................................................................................................................................................ 16
4.1.2.1 Idaho PV Adoption by Sector ...................................................................................................................... 19
4.1.3 Oregon ............................................................................................................................................................. 20
4.1.3.1 Oregon PV Adoption by Sector ................................................................................................................... 23
4.1.4 Utah .................................................................................................................................................................. 24
4.1.4.1 Utah PV Adoption by Sector ....................................................................................................................... 27

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4.1.5 Washington....................................................................................................................................................... 28
4.1.5.1 Washington PV Adoption by Sector ............................................................................................................ 30
4.1.6 Wyoming .......................................................................................................................................................... 31
4.1.6.1 Wyoming PV Adoption by Sector ................................................................................................................ 33
APPENDIX A TECHNOLOGY ASSUMPTIONS AND INPUTS ......................................................................................... 34
APPENDIX B DETAILED RESULTS ................................................................................................................................. 35
APPENDIX C WASHINGTON COGENERATION LEVELIZED COSTS ............................................................................ 36
APPENDIX D OREGON DISTRIBUTION SYSTEM PLAN RESULTS .............................................................................. 38
D.1 Study Methodologies and Approaches ................................................................................................................... 39
D.1.1 State-Level Forecast Approach ........................................................................................................................ 39
D.1.2 Circuit-Level Forecasting Approach .................................................................................................................. 40
D.2 Private Generation Forecast Results ..................................................................................................................... 40
D.2.1 Circuit-Level and Substation-Level Results Findings ........................................................................................ 41
D.3 Conclusions ............................................................................................................................................................ 44
D.3.1 Future Work ...................................................................................................................................................... 45
APPENDIX E BEHIND-THE-METER BATTERY STORAGE FORECAST ........................................................................ 46
E.1 Study Methodologies and Approaches ................................................................................................................... 46
E.1.1 Battery Dispatch Modelling ............................................................................................................................... 47
E.2 Results ................................................................................................................................................................... 47
E.3 Storage Capacity Results by State ......................................................................................................................... 49

List of Figures

Figure 1-1 Historic Cumulative Installed Private Generation Capacity, PacifiCorp, 2012-2021 .............................................. 8
Figure 1-2 Methodology to Determine Market Potential of Private Generation Adoption ...................................................... 10
Figure 1-3 Cumulative New Capacity Installed by Scenario (MW-AC), 2023-2042 ............................................................... 11
Figure 1-4 Cumulative New Capacity Installed by State (MW-AC), 2023-2042, Base Case ................................................. 12
Figure 1-5 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Base Case ....................................... 13
Figure 2-1 PacifiCorp Service Territory ................................................................................................................................. 14
Figure 3-1 Example Residential Summer Load Shape Compared to PV Only and PV + Battery Generation Profiles .......... 17
Figure 3-2 Cost of Residential PV Standalone, Battery Storage Retrofit to Existing PV, and PV + Battery Systems from DNV Bottom-up Cap-Ex Model, Utah .............................................................................................................................................. 21
Figure 3-3 Cost of Commercial PV Standalone, Battery Storage Retrofit to Existing PV, and PV + Battery Systems from DNV Bottom-up Cap-Ex Model, Utah .............................................................................................................................................. 21
Figure 3-4 Average Residential Solar PV System Costs, 2023-2042.................................................................................... 22
Figure 3-5 Average Non-Residential Solar PV System Costs, 2023-2042 ............................................................................ 23

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Figure 3-6 Average Residential Battery Energy Storage System (AC-Coupled) Costs, 2023-2042 ...................................... 23
Figure 3-7 Average Non-Residential Battery Energy Storage System (AC-Coupled) Costs, 2023-2042 .............................. 23
Figure 3-8 Historic Cumulative Installed Private Generation Capacity by Technology, YTD ................................................... 2
Figure 3-9 Methodology to Determine Market Potential of Private Generation Adoption ........................................................ 3
Figure 3-10 Bass Diffusion Curve Illustration .......................................................................................................................... 6
Figure 3-11 Willingness to Adopt Based on Technology Payback .......................................................................................... 8
Figure 4-1 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), 2023-2042 .................................. 9
Figure 4-2 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Base Case ....................................... 10
Figure 4-3 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Low Case ........................................ 10
Figure 4-4 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, High Case ........................................ 11
Figure 4-5 Cumulative New Capacity Installed by State (MW-AC), 2023-2042, Base Case ................................................. 12
Figure 4-6 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), California, 2023-2042 ............... 12
Figure 4-7 Cumulative New Capacity Installed by Technology (MW-AC), California Base Case, 2023-2042 ....................... 13
Figure 4-8 Cumulative New Capacity Installed by Technology (MW-AC), California Low Case, 2023-2042 ........................ 13
Figure 4-9 Cumulative New Capacity Installed by Technology (MW-AC), California High Case, 2023-2042 ........................ 14
Figure 4-10 Cumulative New PV Capacity Installed by Sector Across All Scenarios, California, 2023-2042 ........................ 15
Figure 4-11 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Idaho, 2023-2042 ................... 16
Figure 4-12 Cumulative New Capacity Installed by Technology (MW-AC), Idaho Base Case, 2023-2042 ........................... 17
Figure 4-13 Cumulative New Capacity Installed by Technology (MW-AC), Idaho Low Case, 2023-2042 ............................ 17
Figure 4-14 Cumulative New Capacity Installed by Technology (MW-AC), Idaho High Case, 2023-2042 ............................ 18
Figure 4-15 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Idaho, 2023-2042 .............................. 19
Figure 4-16 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Oregon, 2023-2042 ................ 20
Figure 4-17 Cumulative New Capacity Installed by Technology (MW-AC), Oregon Base Case, 2023-2042 ........................ 21
Figure 4-18 Cumulative New Capacity Installed by Technology (MW-AC), Oregon Low Case, 2023-2042 .......................... 21
Figure 4-19 Cumulative New Capacity Installed by Technology (MW-AC), Oregon High Case, 2023-2042 ......................... 22
Figure 4-20 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Oregon, 2023-2042 ........................... 23
Figure 4-21 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Utah, 2023-2042 .................... 24
Figure 4-22 Cumulative New Capacity Installed by Technology (MW-AC), Utah Base Case, 2023-2042 ............................ 25
Figure 4-23 Cumulative New Capacity Installed by Technology (MW-AC), Utah Low Case, 2023-2042 .............................. 25
Figure 4-24 Cumulative New Capacity Installed by Technology (MW-AC), Utah High Case, 2023-2042 ............................. 26
Figure 4-25 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Utah, 2023-2042 ............................... 27
Figure 4-26 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Washington, 2023-2042 ......... 28
Figure 4-27 Cumulative New Capacity Installed by Technology (MW-AC), Washington Base Case, 2023-2042 ................. 28
Figure 4-28 Cumulative New Capacity Installed by Technology (MW-AC), Washington Low Case, 2023-2042 ................... 29
Figure 4-29 Cumulative New Capacity Installed by Technology (MW-AC), Washington High Case, 2023-2042 .................. 29
Figure 4-30 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Washington, 2023-2042 .................... 30
Figure 4-31 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Wyoming, 2023-2042 ............. 31

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Figure 4-32 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming Base Case, 2023-2042 ..................... 31
Figure 4-33 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming Low Case, 2023-2042 ....................... 32
Figure 4-34 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming High Case, 2023-2042 ...................... 32
Figure 4-35 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Wyoming, 2023-2042 ........................ 33
Figure D-1 Historic Cumulative Installed PG Capacity by Technology, PacifiCorp, Oregon, 2012-2021 ............................... 38
Figure D-2 Methodology to Determine Market Potential of Private Generation Adoption ...................................................... 39
Figure D-3 Private Generation Forecast by Technology, PacifiCorp Oregon, All Cases ........................................................ 40
Figure D-4 Private Generation Forecast Disaggregation by Operating Area, PacifiCorp Oregon, Base Case ....................... 41
Figure D-5 Private Generation Forecast Disaggregation by Substation, PacifiCorp Oregon, Base Case .............................. 41
Figure D-6 Private Generation Forecast Disaggregation by Circuit, PacifiCorp Oregon, Base Case ..................................... 42
Figure D-7 Customer Mix of Top Five Substations Compared to the Average of All Substations .......................................... 42
Figure D-8 Customer Attributes of Selected Substations Compared to Average PacifiCorp Oregon Substation ................... 43
Figure D-9 Share of Residential Customers vs. Share of Residential PV Only Capacity in 2033, Klamath Falls Operating
Area ........................................................................................................................................................................................ 44
Figure E-1 Historic Cumulative Installed Behind-the-Meter Battery Storage Capacity, PacifiCorp, 2012-2021 ..................... 46
Figure E-2 Cumulative New Battery Storage Capacity Installed by Scenario (MW), 2023-2042 ............................................ 48
Figure E-3 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, Base Case .................... 48
Figure E-4 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, Low Case ..................... 49
Figure E-5 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, High Case ..................... 49
Figure E-6 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, Base Case .............................. 50
Figure E-7 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, Low Case ............................... 50
Figure E-8 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, High Case ............................... 51
Figure E-9 Cumulative New Battery Storage Capacity Installed by Scenario (MW), California, 2023-2042 ........................... 51
Figure E-10 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), California, 2023-2042 ............................................................................................................................................................................... 52
Figure E-11 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Idaho, 2023-2042 ............................... 53
Figure E-12 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Idaho, 2023-2042 ........................................................................................................................................................................................ 53
Figure E-13 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Oregon, 2023-2042 ............................ 54
Figure E-14 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Oregon, 2023-2042 ........................................................................................................................................................................................ 55
Figure E-15 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Utah, 2023-2042 ................................ 56
Figure E-16 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Utah, 2023-
2042 ........................................................................................................................................................................................ 56
Figure E-17 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Washington, 2023-2042 ..................... 57
Figure E-18 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Washington,
2023-2042 ............................................................................................................................................................................... 58
Figure E-19 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Wyoming, 2023-2042 ......................... 59
Figure E-20 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Wyoming, 2023-2042 ............................................................................................................................................................................... 59

DNV – www.dnv.com Page vi

List of Tables

Table 3-1 Residential PV Only Representative System Assumptions .................................................................................... 17
Table 3-2 Non-Residential PV Only Representative System Assumptions ............................................................................ 18
Table 3-3 Residential PV + Battery Representative System Assumptions ............................................................................. 19
Table 3-4 Small Wind Assumptions ...................................................................................................................................... 24
Table 3-5 Small Hydro Assumptions ..................................................................................................................................... 24
Table 3-6 Reciprocating Engine Assumptions ...................................................................................................................... 25
Table 3-7 Microturbine Assumptions ...................................................................................................................................... 26
Table 3-8 Motivators and Barriers for Private Generation Technology Adoption .................................................................. 27
Table 3-9 Federal Investment Tax Credits for DERs............................................................................................................... 1
Table 3-10 State Incentives for DERs ..................................................................................................................................... 1
Table 3-11 PG Forecast Economic Analysis Inputs ................................................................................................................. 4
Table 3-12 Solar Willingness-to-Adopt Curve used by State and Sector ................................................................................ 7
Table 4-1 Cumulative Adopted Private Generation Capacity by 2042, by Scenario ................................................................ 9
Table C-1 Reciprocating Engine LCOE Assumptions ............................................................................................................ 36
Table C-2 Microturbine Engine LCOE Assumptions .............................................................................................................. 36
Table C-3 LCOE Results for CHP Systems in Washington State .......................................................................................... 37
Table E-1 Cumulative Adopted Battery Storage Capacity by 2042, by Scenario ................................................................... 47

DNV – www.dnv.com Page vii

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DNV – www.dnv.com February 2, 2023 Page 8

1 EXECUTIVE SUMMARY
DNV prepared the Long-Term Private Generation (PG) Resource Assessment for PacifiCorp (the Company) covering their
service territories in Utah, Oregon, Idaho, Wyoming, California, and Washington to support PacifiCorp’s 2023 Integrated
Resource Plan (IRP). This study evaluated the expected adoption of behind-the-meter (BTM) distributed energy resources
(DERs) including photovoltaic solar (PV only), photovoltaic solar coupled with battery storage (PV + Battery), small wind,
small hydro, reciprocating engines and microturbines over a 20-year forecast horizon (2023-2042) for all customer sectors
(residential, commercial, industrial, and agricultural). The adoption model DNV developed for this study is calibrated to the
current1 installed and interconnected capacity of these technologies, shown in Figure 1-1.
Figure 1-1 Historic Cumulative Installed Private Generation Capacity, PacifiCorp, 2012-2021
Historic Cumulative Installed PG Capacity by State Historic Cumulative Installed PG Capacity by Technology

To date, the majority of PG installed capacity and annual growth in capacity has been in Utah, which represents the largest
portion go PacifiCorp’s customer population—about 50% of all PacifiCorp customers are in the Company’s Utah service
territory. Roughly 99 percent of existing private generation capacity installed in PacifiCorp’s service territory is PV or PV +
Battery. To inform the adoption forecast process, DNV conducted an in-depth review of the other technologies and did not
find any literature to suggest that they would take on a larger share of the private generation market in the Company’s
service territory in the future years of this study.
For each technology and sector, DNV developed three adoption scenarios: a base case, a high case, and a low case. The
base case is considered the most likely projection as it is based on current market trends and expected changes in
technology costs and retail electricity rates; the high and low cases are used as sensitivities to test how changes in costs
and retail rates impact customer adoption of these technologies.

1 PacifiCorp private generation interconnection data as of February 2022.
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Reciprocating Engine0.0%
Micro Turbine0.1%

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All scenarios use technology cost and performance assumptions specific to each state in PacifiCorp’s service territory in the
base year (2022) of the study. The base case uses the 2022 federal income tax credit schedules2 and state incentives, retail
electricity rate escalation from the AEO3 reference case, and a blended version of the NREL Annual Technology Baseline4
moderate and conservative technology cost forecasts as inputs to the modelling process. In the high case, retail electricity
rates increase more rapidly, and technology costs decline at a faster rate compared to the base case. For the low case,
retail electricity rates increase at a slower rate than the base case and technology costs decrease at a slower rate.
1.1 Study Methodologies and Approaches
The forecasting methodologies and techniques applied by DNV in this analysis are commonly used in small-scale, behind-
the-meter energy resource and energy efficiency forecasting. The methods used to develop the state and sector-level
results are described in more detail below.
1.1.1 State-Level Forecast Approach
DNV developed a behind-the-meter net economic perspective that includes, as costs, the acquisition and installation costs
for each technology less the impact of available incentives and, as benefits, the customer’s economic benefits of ownership
such as energy and demand savings and export credits. For this study we assumed that the current net metering or net
billing policies and tariff structures in each state continued throughout the study horizon. This resulted in the model
incorporating benefits associated with net metering in Oregon, Washington, and Wyoming and net billing in Utah and
California. We assumed customers in Idaho would accrue benefits based on the net billing policy in Utah throughout the
study.
This analysis incorporated the current rate structures and tariffs offered to customers in PacifiCorp’s service territories. Time-
of-use rates, tiered tariffs and retail tariffs that include high demand charges increased the value of PV + Battery
configurations compared to PV-Only configurations while other factors such as load profiles and DER compensation
mechanisms minimized the impact of such tariffs on the customer economics of PV + Battery systems. The DER
compensation mechanism in Oregon, Washington, and Wyoming — traditional net metering — does not incentivize PV +
Battery storage co-adoption. In net metering DER compensation schemes, customers receive export credits for excess PV
generation at the same dollar-per-kWh rate that they would have otherwise paid to purchase electricity from the grid. Net
billing—the mechanism modelled in California, Idaho, and Utah—does incentivize PV + Battery storage co-adoption, as
customers can lower their electricity bills by charging their batteries with excess PV generation and dispatching their
batteries to meet on-site load during times of day when retail energy prices are high. From the perspective of utility bill
savings alone, PV + battery systems are often not the most cost-effective option for most customers. Customers who seek
the reassurance and reliability of backup power show more of a willingness to pay for this product, especially if they reside in
areas that are prone to outages and severe weather events.
DNV combined technical feasibility characteristics of the identified PG technologies and potential customers with an
economic analysis to calculate cost-effectiveness metrics for each technology, within each state that PacifiCorp serves, over
the analysis timeframe. DNV then used a bass diffusion model to estimate customer PG adoption based on technical and

2H.R.5376 - Inflation Reduction Act of 2022 (https://www.congress.gov/bill/117th-congress/house-bill/5376/text). Since the passing of the Inflation Recovery Act of 2022, the federal Investment Tax Credit (ITC) has been extended past its original expiration date for ten years. For facilities beginning construction before January 1, 2025, the bill will extend the ITC for up to 30 percent of the cost of installed equipment for ten years and will then step down to 26 percent in 2033 and 22 percent in 2034.
3U.S. Energy Information Administration, Annual Energy Outlook 2022 (AEO2022), (Washington, DC, March 2022).
4NREL (National Renewable Energy Laboratory). 2021. 2021 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory.

DNV – www.dnv.com February 2, 2023 Page 10

economic feasibility and incorporated existing adoption of each PG technology by state and customer segment as an input
to the adoption model.
Technical feasibility characteristics were used to identify the potential customer base that could technically support the
installation of a specific PG technology, or the maximum, feasible, adoption for each technology by sector. These factors
included overall PG metrics such as average customer load shapes and system size limits by state, and specific technology
factors such as estimated rooftop space and resource access based on location (for hydro and wind resource applicability).
Simple payback was used in the customer adoption portion of the model as an input parameter to bass diffusion curves that
determined future penetration of all PG technologies. The methodology and major inputs to the analysis are shown in
Figure 1-2. Changes to technology costs and retail electricity rates used in the high and low cases impact the economic
portion of the analysis.
Figure 1-2 Methodology to Determine Market Potential of Private Generation Adoption

DNV developed Bass diffusion curves customized for each technology, state, and sector that also accounted for variation in
willingness-to-adopt as cost effectiveness changes over time. The Bass diffusion curves were used to model annual and
cumulative market adoption. Bass diffusion curves are widely used for forecasting technology adoption. Diffusion curves
typically take the form of an S-curve with an initial period of slow early adoption that increases as the technology becomes
more mainstream and eventually tapers off amongst late adopters. The upper limit of the curve is set to the maximum level
of market adoption. In this analysis, the long-term maximum level of market adoption was based on payback. As payback
was calculated by year in the economic analysis to capture the changing effects of market interventions over time, the
maximum level of market adoption in the diffusion curves vary by year in the study.
The Bass diffusion curves used in the market potential analysis are characterized by three parameters—an innovation
coefficient, an imitation coefficient, and the ultimate market potential. Together, these three parameters also determine the
time to reach maximum adoption and overall shape of the curve. The innovation and imitation parameters were calibrated
for each technology and sector, based on current market penetration and when PacifiCorp started to see the technology
being adopted in each of its service territories. The calibrated curves show some segments still in the very early phases of
adoption, while other markets are more mature.
Market Potential
Economic Analysis
Technology costs
Installation and O&M costs
Local and federal incentives
Benefits of ownership
Energy savings
Net billing, net metering export credits
Technical Feasibility
System performance constraints
Customer load shapes
System size limits
Land-use requirements
Non-shaded rooftop space
Access to unprotected streams and dams, wind resource

DNV – www.dnv.com February 2, 2023 Page 11

1.2 Private Generation Forecast
In the base case scenario, DNV estimates 3,181 MW of new private generation capacity will be installed in PacifiCorp’s
service territory over the next twenty years (2023-2042). Figure 1-3 shows the base, low and high case scenarios. The low
case scenario estimates 2,028 MW of new capacity over the 20-year forecast while the high case estimates 3,196 MW of
new private generation capacity installed by 2042.
Figure 1-3 Cumulative New Capacity Installed by Scenario (MW-AC), 2023-2042

The sensitivity analysis showed a much greater margin of uncertainty on the low side than the high side. The Inflation
Reduction Act of 2022 (IRA) extends tax credits for private generation that create very favorable economics for adoption,
and those are embedded in the base case. We therefore limited our upper bound forecast to lower technology costs and
higher retail electricity rates, and these produced only a small boost to adoption for technologies that were already cost
effective under the IRA. In contrast, when we modelled our lower bound, we found that the increases to customer payback
period were enough to tamp down adoption by a wider margin. The low case assumed higher technology costs and lower
retail electricity rates than the other cases, reducing the economic appeal of private generation despite incentives being
unchanged. The low case forecast is 36% less than the base case, while the high case cumulative installed capacity
forecasted over the 20-year period is just 0.5% greater than the base case.
Figure 1-4 shows the base case forecast by state, compared to the previous (2020) study’s total base case forecast.5 This
figure indicates that Utah and Oregon will drive most PG installations over the next two decades, which is to be expected
given these two states represent the largest share of PacifiCorp’s customers and sales. The base scenario estimates
approximately 1,447 MW of new capacity will be installed over the next 10 years in PacifiCorp’s territory—55% of which is in
Utah, 32% in Oregon, and 6% in Idaho. Since the 2020 study, the federal Investment Tax Credit (ITC) has been extended
for ten years at its original base rate levels and expanded to include energy storage. The tax credit increase and extension
lowered the customer payback period for all technologies, making the customer economics of this study’s base case more
5 Cumulative capacity is adjusted to account for the difference in the forecast starting years (2021 in the previous study, versus 2023 in this study). Source: Navigant. 2020. “Private Generation Long-Term Resource Assessment (2021-2040)”
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similar to the previous study’s high case. In addition to the change in customer economics, projected PV capacity is
expected to grow at a faster rate in the early years and at a slower rate towards the end of the forecast period. The key
drivers of these differences include larger average PV system sizes, a steeper decline in PV + Battery costs at the start of
the forecast period, and the maturity of rooftop PV technology.
Figure 1-4 Cumulative New Capacity Installed by State (MW-AC), 2023-2042, Base Case

In Figure 1-5 below, the base case forecast is presented by technology for all states in PacifiCorp’s service territory. First
year PV Only is estimated to grow by 76 MW and PV + Battery by 3 MW. These two technologies make up 99% of new
installed private generation capacity forecasted. The results section of the report contains results by technology for the high,
base, and low sectors. Additionally, total PV capacity forecasted is presented by sector in that section as well.
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Figure 1-5 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Base Case

.

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2 STUDY BACKGROUND
DNV prepared this Private Generation Long-term Resource Assessment on behalf of PacifiCorp and representing their
service territory in six states—shown in Figure 2-1—California, Idaho, Oregon, Utah, Washington, and Wyoming. In this
study, private generation technologies provide behind-the-meter energy generation at the customer site and are designed
for the purpose of offsetting customer load and/or peak demand. The purpose of this study is to support PacifiCorp’s 2023
Integrated Resource Plan by projecting the level of private generation resources PacifiCorp’s customers may install over the
next two decades under base, low, and high adoption scenarios. In addition to private generation, DNV also considered the
cost-effective potential for high-efficiency cogeneration in Washington, consistent with the 480-109-060 (13) and 480-109-
100 (6) of the Washington Administrative Code (WAC).
Figure 2-1 PacifiCorp Service Territory

Although there have been six previous studies involving private generation, DNV developed its assumptions, inputs,
methodologies, and forecasts independently from these prior assessments that had been performed for PacifiCorp. The
forecasting methodologies and techniques applied by DNV in this analysis are commonly used in small-scale, behind-the-
meter energy resource and energy efficiency forecasting. This study evaluated the expected adoption of behind-the-meter
technologies over the next 20 years, including:
1. Photovoltaic (Solar PV) Systems
2. Solar PV Paired with Battery Storage
3. Small Scale Wind
4. Small Scale Hydro
5. Reciprocating Engines

Pacific Power

Rocky Mountain Power
WASHINGT ON
IDAHO
CALIFORNIA
WYOMING
UT AH
OREGON

DNV – www.dnv.com February 2, 2023 Page 15

6. Microturbines
Project sizes were determined based on average customer load across the commercial, irrigation, industrial and residential
customer classes for each state. The project sizes were then limited by each state’s respective system size limits. Private
generation adoption for each technology was estimated by sector in each state in PacifiCorp’s service territory.

DNV – www.dnv.com February 2, 2023 Page 16

3 STUDY APPROACH AND METHODS
DNV used applicability/ technical feasibility, customer perspectives towards PGs, and project economics as the basis for
forecasting expected market adoption of each private generation technology.
3.1 Technology Attributes
The technology attributes define the reference systems and their key attributes such as capacity factors, derate factors, and
costs which are used in thepayback and adoption analyses. A full list of detailed technology attributes and assumptions by
state and sector is provided in Appendix A. The following information provides a high-level summary of the key elements of
the technologies assessed in this analysis.
3.1.1 Solar PV
Solar photovoltaic (PV) systems convert sunlight into electrical energy. DNV modeled representative PV system energy
output for residential and non-residential systems in each state to estimate first-year production. To model hourly production,
DNV leveraged its SolarFarmer and Solar Resource Compass APIs. DNV’s Solar Resource Compass API accesses and
compares irradiance data from multiple data providers in each region. Solar Resource Compass also generates monthly
soiling loss estimates for both dust soiling and snow soiling, as well as a monthly albedo profile. By incorporating industry
standard models and DNV analytics, precipitation and snowfall data is automatically accessed and used to estimate the
impact on energy generation.
Total PV capacity is forecasted by two different technology configurations: PV Only and PV + Battery.The PV technology in
the PV + Battery systems were modeled using the same specifications as the PV Only technology, with the exception of
nameplate capacity. DNV determined that average system sizes for PV + Battery configurations are on average larger than
PV Only systems.
DNV further segmented the PV + Battery technology by new PV + Battery systems installed together and a Battery Retrofit
case—where a battery is added to an existing PV system. The PV Only forecast presented in the results section of this
report is net of customers who later adopt an add-on battery system (Battery Retrofit), and therefore become a part of the
PV + Battery forecast. DNV assumes that customers in the Battery Retrofit case do not represent new incremental PV MW-
AC capacity, however the generation profile of the customer changes from PV Only to PV + Battery.
An example residential customer load profile for two summer days is presented in Figure 3-1 to illustrate the difference
between the generation profiles of PV Only and PV + Battery systems in this analysis.

DNV – www.dnv.com February 2, 2023 Page 17

Figure 3-1 Example Residential Summer Load Shape Compared to PV Only and PV + Battery Generation Profiles

3.1.1.1 PV Only
Table 3-1 provides the representative system specifications used to model residential standalone PV adoption. DC/AC ratio
assumptions are derived from DNV's experience in the residential PV industry.
Table 3-1 Residential PV Only Representative System Assumptions
System
Performance Units CA ID OR UT WA WY
Nameplate Capacity kW-DC 6.5 6.0 6.8 5.5 10.0 5.5
Module Type n/a c-Si c-Si c-Si c-Si c-Si c-Si
PV Inverter n/a Microinverter
Installation Requirements n/a Fixed-tilt Roof Mounted
Capacity Factor kWh/(kW-DC x 8760 hrs/yr) 13% 15% 16% 15% 13% 16%
DC/AC Derate Factor n/a 1.118 1.123 1.121 1.129 1.132 1.118
0.00
1.00
2.00
3.00
4.00
5.00
6.00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47
Po
w
e
r

(
k
W
)
Hour of Day (Hour Ending MT)
Customer Load (Gross)PV Only Generation (Gross)PV + Battery Generation (Net Effective)

DNV – www.dnv.com February 2, 2023 Page 18

Table 3-2 provides the representative system specification used to model non-residential standalone PV adoption. DC/AC
ratio assumptions are derived from Wood Mackenzie's H1 2022 US solar PV system pricing report. The nameplate capacity
of the system is dependent on the average customer size for each non-residential sector and state.
Table 3-2 Non-Residential PV Only Representative System Assumptions
System
Performance Units CA ID OR UT WA WY
Nameplate Capacity kW-DC 30-150 37-100 30-115 60-750 20-100 18-25
Module Type n/a c-Si c-Si c-Si c-Si c-Si c-Si
PV Inverter n/a Three-phase string inverter
Installation Requirements n/a Flat Roof Mounted
Capacity Factor kWh/(kW-DC x 8760 hrs/yr) 14% 13% 12% 14% 12% 12%
DC/AC Derate Factor n/a 1.30 1.30 1.30 1.30 1.30 1.30
The full list of nameplate capacity assumptions by sector and state can be found in Appendix A. For all PV systems, DNV
assumed a linear degradation rate of 0.5% across the expected useful life of the system.
3.1.1.2 PV + Battery
Technology attributes consist of a representative system, operational data, cost assumptions, and capital costs which are
used in conjunction to develop a total installed cost in dollars per kW. DNV reviewed PacifiCorp’s history of interconnected
projects to develop its customer level assumptions for number of batteries, usable energy capacity, and rated power at the
state level. The resulting representative composite system is used for operational parameters and costs to be used for long-
term adoption and forecasting purposes.
DNV assumes a fully integrated battery energy storage system (BESS) product for the residential sector, which will include a
battery pack and a bi-directional inverter based on leading residential battery energy storage manufacturers such as Tesla,
Enphase, and Sonnen providing fully integrated BESS solutions. Table 3-3 presents the representative residential PV +
Battery system assumptions used in this analysis. The system specifications for the commercial, industrial, and irrigation
sector are listed in Appendix A.

DNV – www.dnv.com February 2, 2023 Page 19

Table 3-3 Residential PV + Battery Representative System Assumptions
Technology System Performance Units CA ID OR UT WA WY
PV Nameplate Capacity kW-DC 9.5 8.8 10.6 8.1 13.6 8.6
BESS
Total Usable Energy Capacity kWh 12.5 12.5 14.0 12.5 14.0 10.0
Total Power kW 5.0 5.0 7.0 5.0 7.0 5.0
Battery Duration Hrs 2.5 2.5 2.0 2.5 2.0 2.0
Roundtrip Efficiency % 89%
Battery Pack Chemistry n/a Lithium-ion NMC (Nickel, Manganese, Cobalt)
Residential and non-residential BESS can be installed as a standalone system, added to an existing PV system, or the
system can be installed with a new PV system. DNV assumed all battery installations would be co-located with a PV system
in an AC-coupled configuration, as standalone systems are ineligible for the federal ITC—explained further in section 3.2.5.
Battery adoption was forecasted separately for PV + Battery systems installed together, and the Battery Retrofit case—
where a battery is added to an existing PV system. The basis of the Battery Retrofit forecast is the existing PV capacity in
PacifiCorp’s service territories and the PV Only capacity forecasted in this analysis. For the purpose of forecasting private
generation capacity, the Battery Retrofit forecast is presented in the results section as a part of the PV + Battery capacity
forecast. In the behind-the-meter battery storage capacity forecast, presented in Appendix E, the Battery Retrofit case is split
out in the presentation of the results.
Battery degradation was modeled using DNV’s Battery AI, a data-driven battery analytics tool that predicts short-term and
long-term useable energy capacity degradation under different usage conditions. It combines laboratory cell testing data with
artificial intelligence (AI) technologies to provide an estimation for battery energy capacity degradation over time. In this
analysis, Battery AI models several current-generation, commercially available Nickel Manganese Cobalt (NMC) cells were
used to predict expected degradation performance of “generic” cells. These cells were tested in the lab over periods of 6 –
12 months at multiple temperatures, C-rates, SOC ranges, and cycling/resting conditions. Predictions are generally
constrained to within the bounds of the testing data. DNV has not explicitly modeled battery end-of-life (EOL), due to a lack
of testing data in this region of operation. Earlier of 20-years or 60% capacity retention is generally considered to represent
EOL.
Both cycling and calendar effects were considered in the degradation assessment. It is also assumed the battery cell
temperature will be controlled to be around 25°C for majority of the time with proper thermal management (ventilation,
HVAC). DNV notes that temperature plays a key role in battery degradation. Continuous operation under extreme low or
high temperatures will accelerate degradation in battery state of health.
Cost Assumptions
Cost assumptions are used in conjunction with representative system parameters to develop system costs. The costs are
developed for each state and sector, inclusive of hardware, labor, permitting and interconnection fees, as well as provisions
for sales and marketing, overhead, and profit. For labor costs, we used state level data from the US Bureau of Labor
Statistics (BLS) for electricians, laborers (construction), and electrical engineers.

DNV – www.dnv.com February 2, 2023 Page 20

Total installed costs (or capital expenditures) are based on cost assumptions that were developed on a bottom-up basis—
including hardware, installation/interconnection, as well as a provision for sales, general, and administrative costs and
overhead. Capital expenditures (Cap-Ex) are expenditures required to achieve commercial operation in a given year. Pricing
is indicative of a cash sale, not a lease or PPA, and it does not account for ITC or local rebates. Examples of total installed
costs by category for residential and commercial customers in Utah are shown in Figure 3-2 and Figure 3-3, respectively.
The full set of cost and incentive assumptions used in the analysis can be found in Appendix A.

DNV – www.dnv.com February 2, 2023 Page 21

Figure 3-2 Cost of Residential PV Standalone, Battery Storage Retrofit to Existing PV, and PV + Battery Systems
from DNV Bottom-up Cap-Ex Model, Utah

Figure 3-3 Cost of Commercial PV Standalone, Battery Storage Retrofit to Existing PV, and PV + Battery Systems
from DNV Bottom-up Cap-Ex Model, Utah

DNV has estimated all CapEx categories for the projects based on Wood Mackenzie's US 2022 H1 cost model, which has
been found to be reasonable relative to actual CapEx that DNV has observed on projects it's reviewed in the past. DNV
estimated the benchmark CapEx values based on the project capacity, location, and technology assumptions for each state
and sector. When technology assumptions were unavailable, DNV made reasonable assumptions. Combined PV + Battery
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
$35,000
PV Only (8 kW) Battery Retrofit (5 kW/12.5kWh)PV (8 kW) + Battery (5kW/12.5 kWh)
20
2
2

U
S
D
Overhead & Profit
Sales Tax
Supply Chain and Logistics
Customer Acquisition
Permitting, Interconnection, &InspectionDesign & Engineering
Install Labor
Balance of System
Battery Inverter
Battery Pack
PV Inverter
PV Module
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
PV Only (156 kW) Battery Retrofit (35kW/140 kWh)PV (156 kW) + Battery(35 kW/140 kWh)
20
2
2

U
S
D
EPC and DeveloperOverhead & Margin
Sales Tax
Permitting, Interconnection &Inspection
Install Labor and Design &Engineering
Balance of System
Battery Inverter
Battery Pack
PV Inverter
PV Module

DNV – www.dnv.com February 2, 2023 Page 22

systems were assumed to have cost efficiencies in certain categories that would reduce the total cost of the system when
installed at the same time. Cap-Ex categories assumed to have cost efficiencies for combined systems include electrical and
structural balance of system, installation labor, design & engineering, permitting, interconnection & inspection costs,
customer acquisition costs, supply chain and logistics, and overhead and profit costs.
DNV used a blended version of the NREL Annual Technology Baseline6 moderate and conservative solar PV and battery
energy storage system technology cost forecasts in the base case of this private generation forecast. The average
residential and non-residential PV system cost forecasts are presented in Figure 3-4 and Figure 3-5, and the average
residential and non-residential battery cost forecasts are shown in Figure 3-6 and Figure 3-7. DNV reviewed the costs
presented in the NREL dataset and found that the moderate cost decline forecast for solar PV was much more aggressive
than what DNV’s national cost models are predicting and what has been seen in the market historically. The technology cost
forecast used in the base case has a 37% price decrease in the first 10 years, as opposed to the 50% decrease forecasted
in the NREL moderate case.
Figure 3-4 Average Residential Solar PV System Costs, 2023-2042

6NREL (National Renewable Energy Laboratory). 2021. 2021 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory.
-
500
1,000
1,500
2,000
2,500
3,000
3,500
2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
20
2
2
$
/
k
W
-
D
C
Low
Base
High

DNV – www.dnv.com February 2, 2023 Page 23

Figure 3-5 Average Non-Residential Solar PV System Costs, 2023-2042

Figure 3-6 Average Residential Battery Energy Storage System (AC-Coupled) Costs, 2023-2042

Figure 3-7 Average Non-Residential Battery Energy Storage System (AC-Coupled) Costs, 2023-2042

-
500
1,000
1,500
2,000
2,500
2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
20
2
2
$
/
k
W
-
D
C
Low
Base
High
-
200
400
600
800
1,000
1,200
1,400
1,600
2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
20
2
2
$
/
k
W
-
D
C
Low
Base
High
-
100
200
300
400
500
600
2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042
20
2
2
$
/
k
W
-
D
C
Low
Base
High

DNV – www.dnv.com February 2, 2023 Page 24

3.1.2 Small-Scale Wind
Distributed wind technology is a relatively mature DER. Small-scale wind systems typically serve rural homes, farms, and
manufacturing facilities due to their size and land requirements. Wind turbines generate electricity by converting kinetic
energy in the wind into rotating shaft power that spins an AC generator.
Assumptions on system capacity sizes in each state and sector are detailed in Appendix A. Table 3-4 provides the cost and
performance assumptions used in the small-scale wind forecast and the source for each.
Table 3-4 Small Wind Assumptions
Cost &
Performance
Metric
Units
Residential
(20 kW or
less)
Commercial
(21-100 kW)
Midsize
(101-999
kW)
Sources
Installed Cost 2022$/kW $6,185 $4,686 $3,015 NREL, 2022. Distributed Wind Energy Futures Study. https://www.nrel.gov/docs/fy22osti/82519.pdf
Annual Installed Cost Change %, 2022-2042 -1.9% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Fixed O&M 2022$/kW-yr $38 $38 $38 NREL, 2022. Distributed Wind Energy Futures Study. https://www.nrel.gov/docs/fy22osti/82519.pdf
Annual Fixed O&M Cost Change %, 2022-2042 -3.5% -1.9% -1.9% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Capacity Factor (dependent on state)
% 7.7-10.8% 15.1%-18.5% 15.2%-18.4%
System Advisor Model Version 2021.12.2. National Renewable Energy Laboratory. Golden, CO. https://sam.nrel.gov

3.1.3 Small-Scale Hydropower
Hydroelectric power is an established, mature technology, but small-scale systems are a newer permutation of the
technology and therefore are still quite costly compared to other private generation technologies. Small hydro systems
generate electricity by transforming potential energy from a water source into kinetic energy that rotates the shaft of an AC
generator. Assumptions on system capacity sizes in each state and sector are detailed in Appendix A. Table 3-5 provides
the cost and performance assumptions used in the small hydro forecast and the source for each.
Table 3-5 Small Hydro Assumptions
Cost &
Performance
Metric
Units
Micro-
hydro
(100 kW
or less)
Mini-
hydro
(100 kW-1
MW)
Sources
Installed Cost 2022$/kW $5,190 $3,892 International Renewable Energy Agency (IRENA). 2012. "Renewable Energy Cost Analysis: Hydropower"

DNV – www.dnv.com February 2, 2023 Page 25

Annual Installed Cost Change %, 2022-2042 -0.2% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Fixed O&M 2022$/kW-yr $208 $156 International Renewable Energy Agency (IRENA). 2012. "Renewable Energy Cost Analysis: Hydropower"
Annual Fixed O&M Cost Change %, 2022-2042 -1.9% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Capacity Factor % 45% 45% International Renewable Energy Agency (IRENA). 2012. "Renewable Energy Cost Analysis: Hydropower"
3.1.4 Reciprocating Engines
Combined heat and power (CHP), or cogeneration, is a mature technology that has been used in the power sector and as a
private generation resource for decades. The two most common CHP technologies for commercial and small- to medium-
industrial applications are reciprocating engines and microturbines, used to produce both onsite power and thermal energy.
Reciprocating engines are a mature, reliable technology that perform well at part-load operation in both baseload and load
following applications. Reciprocating engines can be operated with a wide variety of fuels; however, this analysis assumes
natural gas is used to generate electricity as it is the most commonly used fuel in CHP applications. A reciprocating engine
uses a cylindrical combustion chamber with a close-fitting piston that travels the length of the cylinder. The piston connects
to a crankshaft that converts the linear motion of the piston into rotating motion. Reciprocating engines start quickly and
operate on normal natural gas delivery pressures without additional gas compression. The thermal energy output from
system operation can be used to produce hot water or low-pressure steam, or chilled water with the additional of an
absorption chiller. Typical CHP applications for reciprocating engine systems in the Pacific Northwest include universities,
hospitals, wastewater treatment facilities, agricultural applications, commercial buildings, and small- to medium-sized
industrial facilities.7
Assumptions on system capacity sizes in each state and sector are detailed in Appendix A. Two representative reciprocating
engine sizes were used in this analysis based on the ability to meet average customer minimum electric load, ranging from
less than 100 kW to 1 MW. Table 3-6 provides the cost and performance assumptions used in the reciprocating engine
forecast and the source for each.
Table 3-6 Reciprocating Engine Assumptions
Cost &
Performance
Metric
Units
Small
(100 kW
or less)
Medium
(100 kW-1
MW)
Sources
Installed Cost 2022$/kW $4,189 $3,183 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.
Annual Installed Cost Change %, 2022-2042 -0.5% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/

7 U.S. Department of Energy Combined Heat and Power and Microgrid Installation Databases (2022). Available at: https://doe.icfwebservices.com/chp

DNV – www.dnv.com February 2, 2023 Page 26

Variable O&M 2022$/MWh $28 $25 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.
Annual Variable O&M Cost Change %, 2022-2042 -1.9% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Electric Heat Rate (HHV) Btu/kWh 11,765 9,721 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.

3.1.5 Microturbines
Microturbines are another CHP application that are commonly used in smaller commercial and inustrial applications. They
are smaller combustion turbines that can be stacked in parallel to serve larger loads and provide flexibility in deployment and
interconnection at customer sites. Microturbines can use gaseous or liquid fuels, but for CHP applications natural gas is the
most common fuel. Therefore for this analysis DNV assumed microturbines will use natural gas to generate electricity and
thermal energy at customer sites. Microturbines operate on the Brayton thermodynamic cycle where atmospheric air is
compressed, heated by burning fuel and then used to drive a turbine that in turn drives an AC generator. A microturbine can
have exhaust temperatures in the range of 500 to 600⁰F, which can be used to produce steam, hot water, or chilled water
with the additional of an absorption chiller in CHP applications. Microturbine efficiency declines significantly as load
decreases, therefore the technology is best suited to operate in base load applications operating at or near full system load.
Common microturbine CHP installations in the Pacific Northwestinclude small universities, commercial buildings, small
manufacturing operations, hotels, and wastewater treatment facilities.7
Assumptions on system capacity sizes in each state and sector are detailed in Appendix A. Two representative microturbine
sizes were used in this analysis based on the ability to meet average customer minimum electric load, ranging from less
than 100 kW to 1 MW. Table 3-7 provides the cost and performance assumptions used in the reciprocating engine forecast
and the source for each.
Table 3-7 Microturbine Assumptions
Cost &
Performance
Metric
Units
Small
(less than
100 kW)
Medium
(100 kW-1
MW)
Sources
Installed Cost 2022$/kW $3,742 $3,686 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.
Annual Installed Cost Change %, 2022-2042 -0.6% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/
Variable O&M 2022$/MWh $19 $15 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.
Annual Variable O&M Cost Change %, 2022-2042 -1.9% NREL. 2021. "2021 Annual Technology Baseline." Golden, CO: National Renewable Energy Laboratory. https://atb.nrel.gov/

DNV – www.dnv.com February 2, 2023 Page 27

Electric Heat Rate (HHV) Btu/kWh 13,648 11,566 "A Comprehensive Assessment of Small Combined Heat and Power Technical and Market Potential in California." 2019. California Energy Commission.

3.2 Customer Perspectives
Customers’ attitudes towards, and general understanding of, private generation technologies, projects, and initiatives
currently being promoted in the market today will vary based on a variety of factors covered in this section. DNV has
combined internal expertise with an aggregation of customer-focused research from reputable sources to understand overall
trends in customer sentiment and insights specifically related to private generation for residential or nonresidential buildings..
Some of the key motivators and barriers to private generation technology adoption are presented in Table 3-8.
Table 3-8 Motivators and Barriers for Private Generation Technology Adoption
TECHNOLOGY MOTIVATORS BARRIERS
ALL  Cost savings
 Reducing carbon footprint
 Educational awareness
 Proactive involvement from customer
 Minimal understanding of technology
applications
SOLAR PV
 Cost savings
 Reducing carbon footprint
 Attractive financing options
 Initial investment
 Infrastructure requirements i.e., physical space
and roof quality
 Perception as a technology for the affluent
BATTERY STORAGE
 Cost savings
 Resilience/backup power
 likelihood to experience to severe weather
 Reduce peak consumption
 Low levels of awareness and understanding
 Short duration capability for backup
 Limited monetization opportunities
 Physical space and roof quality
 Initial investment
 Limited use cases for storage-only
SOLAR + BATTERY
 Resilience/backup power
 ITC applicability window
 Maximize solar generation
 Cost savings
 Reducing carbon footprint
 Initial investment
 Infrastructure requirements of solar
Customer adoption of solar, storage, and other PG-related solutions is primarily influenced by financial viability of the overall
project and the associated return on investment or payback period. However, while the financial parameters and payment
options for a project are certainly an important feature, customers will also face different barriers or motivators that will either
encourage or discourage them from adoption despite the financial benefits.
For these reasons, research organizations have typically viewed adoption of new and innovative technologies by customer
segments ranging from early adopters and enthusiasts to the majority and the laggards. Some customers may even be
considered opposed to the innovation and will never adopt the technology. On the other hand, there also exists a consumer
group that will move forward with adoption of DER offerings even when the financial numbers don’t show the most desirable
ROI or payback. This consumer group is more easilyinfluenced by sales and marketing strategies even when the numbers
don’t “add up” to a clear economic play. The following sections will provide further insights on how customer awareness,

DNV – www.dnv.com February 2, 2023 Page 28

knowledge of energy costs and systems, and incentives can impact customer adoption of PG technologies.

3.2.1 Customer Awareness
While DERs, the term most commonly used to describe PG technologies is a common term within the energy industry, it is
not commonly understood by the average consumer. Less than 10% of residential customers are clear on exactly what the
term means and how it applies to them. Consumers are lacking a sound understanding of how DERs work, the tangible
benefits they provide, and how they would operate within a home or business.
Customer education to build awareness is likely to lead to more growth of PG. Educational outreach and marketing should
focus on accessible, feasible use-cases for technology applications in “real-world” settings that customers can relate to and
see themselves using. Customers have a desire to improve their understanding of PG opportunities by obtaining quality
information – most prefer their electricity provider as the source – about the savings potential of these technologies and
details on how they work. 8
3.2.2 Motivating Factors for Adoption
The primary motivators that prompt customers to consider implementing PG technologies are how much savings they can
realize through a project and the level of incentives being awarded. Second to these financial motivators, customers are
interested in PG opportunities as a method of reducing their environmental impact. Customers who are aware of PG
opportunities often have a curiosity and desire to increase their understanding of the opportunities available to them as
committing to a PG system or product requires the customer to have a greater level of involvement in their electricity
generation, consumption, and management. While understanding and awareness of PG is a clear barrier to adoption,
customers have the desire to obtain information to help them better understand these technologies. Energy providers can
prioritize informative, engaging communication to increase the customers’ understanding of DER opportunities, thus
increasing their likelihood of adoption and participation.7
3.2.3 Barriers to Adoption
Trust and finances are common barriers to PG adoption– customers are often skeptical that these projects will perform as
advertised and save the amount of money that is claimed. Customers need quality information to help them validate the
investment in certain new technologies or programs that they do not have experience with. If the customer’s goal for a PG
system is to save money and they express the need to understand how much money the projects will save, accurate
information needs to be available to prove those cases to the customer. Successful implementation of PG technologies and
solutions will require changing the behavior and perception of a large portion of the customers.7
3.2.4 Other Considerations
Customers who participate in demand response programs are more likely to own a hybrid or electric vehicle, energy
management system (EMS), or solar + storage system than customers who do not participate in demand response
programs. A foundational piece for growing participation in DER initiatives can be first focusing on demand response
programs as a way for customers to get started on their clean energy journeys. This concept of “DER stacking” enables a
utility to prioritize targeting customers who are already participating in some form of demand response or PG-related
program, thus giving the customer a more holistic solution for their energy management and consumption.7

8 SECC (Smart Energy Consumer Collaborative). 2019. Distributed Energy Resources: MEETING CONSUMER NEEDS. Pages 7 – 13.

DNV – www.dnv.com February 2, 2023 Page 29

3.2.5 Incentives Overview
Since the passing of the Inflation Recovery Act of 2022, the federal Investment Tax Credit (ITC) has been extended past its
original expiration date for ten years. For facilities beginning construction before January 1, 2025, the bill will extend the ITC
for up to 30 percent of the cost of installed equipment for ten years and will then step down to 26 percent in 2033 and 22
percent in 2034. For projects beginning construction after 2019 that are placed in service before January 1, 2022, the ITC
would be set at 26 percent. In addition to the new federal ITC schedule for generating facilities, the updated ITC includes
credits for standalone energy storage with a capacity of at least 3 kWh for residential customers and 5 kWh for non-
residential customers. The bill also includes a 5-year MACRS depreciation schedule for non-residential energy storage. The
federal tax credits in Table 3-9 were included in the economic analysis of all private generation forecast scenarios.

DNV – www.dnv.com February 2, 2023 Page 1

Table 3-9 Federal Investment Tax Credits for DERs
Cells in green represent the transition to a technology-neutral ITC for clean energy technologies with 0 gCO2e emissions per kWh, under section 48D.
INCENTIVE SYSTEM
SIZE (KW) TECHNOLOGY 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035+
Residential/
Business ITC < 1000 PV 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 26% 22% 0%
Residential/
Business ITC < 1000 Energy Storage 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 26% 26% 0%
Residential/
Business ITC < 1000 Small Wind 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 26% 22% 0%
Business ITC < 1000 Microturbines 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 26% 22% 0%
Business ITC < 1000 Reciprocating Engines 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 26% 22% 0%
Business ITC < 150 Small Hydro (hydropowered dams) 30% 30% 30%
Business ITC < 25 Small Hydro (Hydrokinetic pressurized conduits) 30% 30% 30%
Business ITC < 1000 Small Hydro 30% 30% 30% 30% 30% 30% 30% 30% 26% 22% 0%
A summary of the state incentives included in the economic analysis are provided below in Table 3-10.

DNV – www.dnv.com February 2, 2023 Page 1

Table 3-10 State Incentives for DERs
STATE RESIDENTIAL NON-RESIDENTIAL
Oregon9
PV-Only:
Up to $5,000
PV + Battery:
Up to $2,500
$0.20/watt up to $20,000
Utah10
PV:
2022—$800
2023—$400
Non-PV:
Up to $2,000
Up to 10 percent of the eligible
system cost or up to $50,000*
Idaho11 Annual maximum of $5,000, and $20,000 over four years** None
California None None
Washington None None
Wyoming None None
* Solar PV, wind, geothermal, hydro, biomass or certain renewable thermal technologies ** Mechanism or series of mechanisms using solar radiation, wind or geothermal resource
3.3 Current Private Generation Market
To date, about 99 percent of existing private generation capacity installed in PacifiCorp’s service territory is PV or PV +
Battery12. To inform the adoption forecast process, DNV conducted an in-depth review of the other technologies and did not
find any literature to suggest that they would take on a larger share of the private generation market in the Company’s
service territory in the future years of this study. Figure 3-8 shows the current share of private generation capacity by
technology in each of PacifiCorp’s six-state service territory.

9 Incentives provided through Energy Trust of Oregon (Solar for Your Home, Solar Within Reach and Solar for Your Business) and Oregon Department of Energy (Solar + Storage Rebate Program for Low-Moderate Income and Non-Income Restricted Homeowners). https://energytrust.org/programs/solar/ https://www.oregon.gov/energy/Incentives/Pages/Solar-Storage-Rebate-Program.aspx
10 Incentives provided through Utah Office of Energy Development Renewable Energy Systems Tax Credit. https://energy.utah.gov/tax-credits/renewable-energy-systems-
tax-credit/
11 Incentives provided through the State of Idaho Renewable Alternative Tax Deduction. https://legislature.idaho.gov/statutesrules/idstat/title63/t63ch30/sect63-3022c/
12 PacifiCorp private generation interconnection data as of February 2022.

DNV – www.dnv.com February 2, 2023 Page 2

Figure 3-8 Historic Cumulative Installed Private Generation Capacity by Technology, YTD

PG Capacity Installed: 12.5 MW-AC PG Capacity Installed: 13.4 MW-AC

PG Capacity Installed: 117.4 MW-AC PG Capacity Installed: 452.3 MW-AC

PG Capacity Installed: 24.2 MW-AC PG Capacity Installed: 4.1 MW-AC
PV Only99%
PV + Battery1%
Wind0%
Small Hydro0%
Reciprocating Engine0%
Micro Turbine0%
CA
PV Only94%
PV + Battery4%
Wind2%
Small Hydro0%
Reciprocating Engine0%
Micro Turbine0%
ID
PV Only97%
PV + Battery2%
Wind0%
Small Hydro0%
Reciprocating Engine0%
Micro Turbine1%
OR
PV Only95%
PV + Battery5%
Wind0%
Small Hydro0%
Reciprocating Engine0%
Micro Turbine0%
UT
PV Only99%
PV + Battery1%
Wind0%
Small Hydro0%
Reciprocating Engine0%Micro Turbine0%
WA
PV Only89%
PV + Battery4%
Wind7%
Small Hydro0%
Reciprocating Engine0%
Micro Turbine0%
WY

DNV – www.dnv.com February 2, 2023 Page 3

Section 3.4.3 describes in further detail how the historic private generation adoption data is used in the private generation
forecast modelling process.
3.4 Forecast Methodology
DNV combined technical feasibility characteristics of the identified PG technologies and potential customers with an
economic analysis to calculate cost-effectiveness metrics for each technology, within each state that PacifiCorp serves, over
the analysis timeframe. DNV then used a bass diffusion model to estimate customer PG adoption based on technical and
economic feasibility and incorporated existing adoption of each PG technology by state and customer segment as an input
to the adoption model.
Technical feasibility characteristics were used to identify the potential customer base that could technically support the
installation of a specific PG technology, or the maximum, feasible, adoption for each technology by sector. These factors
included overall PG metrics such as average customer load shapes and system size limits by state, and specific technology
factors such as estimated rooftop space and resource access based on location (for hydro and wind resource applicability).
Simple payback was used in the customer adoption portion of the model as an input parameter to bass diffusion curves that
determined future penetration of all PG technologies. Figure 3-9 provides a visual representation of how different inputs
were used in different portions of the model. Additional detail on the economic and adoption approaches used in this
analysis are provided in the subsequent sections.
Figure 3-9 Methodology to Determine Market Potential of Private Generation Adoption

3.4.1 Economic Analysis
The economic analysis portion of overall customer adoption was used a key factor in the Bass diffusion model that
calculated future PG adoption. DNV used simple payback as the preferred method of estimating economic viability for PG
based on customer perspectives given its widespread use in similar adoption analyses, ability to reflect customer decision
making in forecasting efforts, and ease of estimation.
DNV developed a behind-the-meter net economic perspective that includes, as costs, the acquisition and installation costs
for each technology less the impact of available incentives and, as benefits, the customer’s economic benefits of ownership
such as energy and demand savings and export credits. For this study we assumed that the current net metering or net
Market Potential
Economic Analysis
Technology costs
Installation and O&M costs
Local and federal incentives
Benefits of ownership
Energy savings
Net billing, net metering export credits
Technical Feasibility
System performance constraints
Customer load shapes
System size limits
Land-use requirements
Non-shaded rooftop space
Access to unprotected streams and dams, wind resource

DNV – www.dnv.com February 2, 2023 Page 4

billing policies and tariff structures in each state continued throughout the study horizon. This resulted in the model
incorporating benefits associated with net metering in Oregon, Washington, and Wyoming and net billing in Utah and
California. We assumed customer’s in Idaho would accrue benefits based on the net billing policy in Utah throughout the
study. DNV has been following the ongoing Idaho Public Utilities Commission (PUC) review of Idaho Power Company’s
(Idaho Power) Value of Distributed Resources (VODER) study filing. Idaho Power’s VODER study found that excess power
generated by rooftop solar owners is worth less than half of retail rate energy and serves as the basis of Idaho Power’s
proposal for a new compensation rate structure for solar owners. If approved by the Idaho PUC, Idaho Power’s proposed
compensation rate structure would more closely resemble the current net billing structure in place in Utah13 and DNV
assumed PacifiCorp would implement a similar rate structure in their Idaho territory.
A detailed breakdown of the simple payback calculation and different elements is shown below.
𝑺𝒊𝒎𝒑𝒍𝒆 𝑷𝒂𝒚𝒃𝒂𝒄𝒌 𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑁𝑒𝑡 𝐶𝑜𝑠𝑡𝑠
𝐶𝑢𝑚𝑢𝑙𝑎𝑡𝑖𝑣𝑒 𝑁𝑒𝑡 𝐵𝑒𝑛𝑒𝑓𝑖𝑡𝑠
𝑪𝒖𝒎𝒖𝒍𝒂𝒕𝒊𝒗𝒆 𝑵𝒆𝒕 𝑪𝒐𝒔𝒕𝒔 𝑈𝑝𝑓𝑟𝑜𝑛𝑡 𝑆𝑦𝑠𝑡𝑒𝑚 𝐶𝑜𝑠𝑡 𝑌𝑒𝑎𝑟 𝑂𝑛𝑒 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒𝑠 𝑁𝑃𝑉𝐴𝑛𝑛𝑢𝑎𝑙 𝑂&𝑀 𝐶𝑜𝑠𝑡𝑠 𝐴𝑛𝑛𝑢𝑎𝑙 𝐹𝑢𝑒𝑙 𝐶𝑜𝑠𝑡𝑠
𝑪𝒖𝒎𝒖𝒍𝒂𝒕𝒊𝒗𝒆 𝑵𝒆𝒕 𝑩𝒆𝒏𝒆𝒇𝒊𝒕𝒔 𝑁𝑃𝑉𝑀𝐴𝐶𝑅𝑆 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 𝑆𝑒𝑙𝑓 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 𝐸𝑥𝑝𝑜𝑟𝑡 𝐶𝑟𝑒𝑑𝑖𝑡𝑠 𝑃𝑒𝑎𝑘 𝐷𝑒𝑚𝑎𝑛𝑑 𝑆𝑎𝑣𝑖𝑛𝑔𝑠
DNV also used an annual hourly profile analysis to estimate electric bill savings and excess generation for each PG
technology by customer segment. This analysis used hourly generation and customer load profiles, and tiered, time-of-use
(TOU), and peak demand rates for each customer and technology permutation. DNV integrated the energy savings, excess
generation, and peak demand benefits into the lifetime simple payback estimation using customer load and individual rate
forecasts provided by PacifiCorp. A full breakdown of all inputs used in the economic analysis is provided in Table 3-11
below.
Table 3-11 PG Forecast Economic Analysis Inputs
INPUT TYPE COST / BENEFIT CATEGORY SOURCE
TECHNOLOGY COST DATA
– INSTALLED COST
PG cost data compiled in $/kW (AC & DC) – used in determining year one
installed system costs DNV
TECHNOLOGY COST DATA
– ANNUAL O&M
PG fixed ($/kW) & variable ($/kWh) O&M data – used in determining annual
system costs DNV
FUEL COST DATA Natural gas cost data ($/MMBtu) EIA Annual Energy
Outlook 2022
TECHNOLOGY
GENERATION PROFILES
Hourly generation profiles for each PG technology by state – used in
calculating self-consumption savings, excess generation credits, and peak
demand savings
DNV
CUSTOMER LOAD
PROFILES
Hourly average customer load profiles by state – used in calculating self-
consumption savings, excess generation credits, and peak demand savings PacifiCorp

13 As of December 19, 2022, the Idaho Power VODER study has been approved by the Idaho PUC. https://puc.idaho.gov/Fileroom/PublicFiles/ELEC/IPC/IPCE2222/OrdNotc/20221219Final_Order_No_35631.pdf

DNV – www.dnv.com February 2, 2023 Page 5

INPUT TYPE COST / BENEFIT CATEGORY SOURCE
CUSTOMER RATES
Customer tiered, TOU, and peak demand rates by size, segment, and state
– used in calculating self-consumption savings, excess generation credits,
and peak demand savings
PacifiCorp
TECHNOLOGY COST
FORECASTS
PG cost data forecasts for installed system costs and annual O&M costs –
used in determining year one installed system costs and future year annual
system costs
NREL ATB
CUSTOMER & LOAD
FORECASTS
Individual customer count and load (kWh) forecasts by segment and state –
used in calculating future year system costs and benefits PacifiCorp
CUSTOMER RATE
FORECASTS
Rate forecasts applied to each customer segment – used in calculating
future year self-consumption savings, excess generation credits, and peak
demand savings
EIA Annual Energy
Outlook 2022

DNV calculated simple payback for each PG technology (solar PV, solar PV + battery, wind, hydro, reciprocating engines,
and microturbines) by applicable individual customer segments (residential, commercial, industrial, and irrigation) for each
installation year in the analysis timeframe (2023 – 2035). These payback results were combined with technical feasibility by
customer segment and integrated into the bass diffusion adoption model to determine annual PG penetration throughout
PacifiCorp’s territory.
3.4.2 Technical Feasibility
The maximum amount of technical feasible capacity of private generation was determined individually for each technology
considered in the private generation forecast. Each technology was generally limited by customer access factors, system
size limits, and energy consumption. The customer load shapes, provided by PacifiCorp, were used to calculate annual
energy use (kWh) cutoffs used in identifying the total number of customers that could technically support the installation of a
specific PG technology. Other data sources specific to each technology were used to determine the amount of capacity that
can be physically installed within PacifiCorp’s service territory, such as:
 Hydropower potential data and environmental attributes for all HUC10 watersheds in PacifiCorp’s service territory14
 Building rooftop hosting area and suitability for solar PV15
 Wind resource potential data by state16

14 Kao, Shih-Chieh, Mcmanamay, Ryan A., Stewart, Kevin M., Samu, Nicole M., Hadjerioua, Boualem, Deneale, Scott T., Yeasmin, Dilruba, Pasha, M. Fayzul K.,
Oubeidillah, Abdoul A., and Smith, Brennan T. New Stream-reach Development: A Comprehensive Assessment of Hydropower Energy Potential in the United States. United States: N. p., 2014. Web. doi:10.2172/1130425.
15 Gagnon, P., R. Margolis, J. Melius, C. Phillips, and R. Elmore. 2016. Rooftop Solar Photovoltaic Technical Potential in the United States: A Detailed Assessment. NREL/TP-6A20-65298. Golden, CO: National Renewable Energy Laboratory.
16 Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. "The Wind Integration National Dataset (WIND) Toolkit." Applied Energy 151: 355366.

DNV – www.dnv.com February 2, 2023 Page 6

3.4.3 Market Adoption
DNV modeled market adoption using Bass diffusion curves customized to each state, technology, and sector. The Bass
diffusion model was developed in the 1960s and is widely used to model market adoption over time.
The formula for new adoption of a technology in year t is given by17
𝑠𝑡 𝑚 𝑝 𝑞
𝑝
𝑒
1 𝑞𝑝𝑒
Where:
s(t) is new adopters at time t
m is the ultimate market potential
p is the coefficient of innovation
q is the coefficient of imitation
t is time in years
Figure 3-10 shows a generalized Bass diffusion curve. The cumulative adoption curve takes a characteristic “S” shape with a
new unknown and unproven technology having relatively slow adoption that accelerates over time as the technology
becomes more familiar to a wider segment of the population. As the pool of potential buyers who have not yet adopted the
technology shrinks, the rate of adoption (as a percent of the total pool of potential adopters) decreases until eventually
everyone who will adopt has adopted. The corresponding chart shows the rate of annual new adoption.
Figure 3-10 Bass Diffusion Curve Illustration

In the illustration, the cumulative curve approaches 60% market penetration asymptotically, corresponding to the value of m
(ultimate market potential) that we chose for the illustration. For our adoption models, we tied the value of m to payback,

17 Bass, Frank (1969). "A new product growth for model consumer durables". Management Science. 15 (5): 215–227
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DNV – www.dnv.com February 2, 2023 Page 7

following Sigrin and Drury’s18 survey findings on willingness to pay for rooftop photovoltaics based on payback. Because
payback varied by technology, state, and sector, so did the Bass diffusion curve.
Due to regional and sectoral differences, we made significant adjustments to the willingness-to-adopt curves to better align
with the observed relationship between historic cost effectiveness and current market adoption by technology, state, and
sector in PacifiCorp’s service territory. Based on PacifiCorp data on current levels of PG adoption, Utah in particular showed
higher adoption than published willingness-to-pay curves would suggest, which we believe may be due to regional variation
in how customers value resilience. To account for this variation across states, we developed three willingness-to-adopt
curves to capture observed state variation. Table 3-12 shows which willingness-to-adopt curve was used for solar for each
state and sector. Current adoption for the other modeled technologies was too low to discern variation across state, so we
assumed average propensity to adopt for wind, small hydro, reciprocating engines and microturbines.
Table 3-12 Solar Willingness-to-Adopt Curve used by State and Sector
AVERAGE PROPENSITY TO
ADOPT
HIGH PROPENSITY TO ADOPT LOW PROPENSITY TO ADOPT
 California residential,
commercial, irrigation
 Idaho residential
 Oregon residential
 Washington all sectors
 Utah all sectors
 Oregon commercial, industrial,
irrigation
 Wyoming all sectors
 Idaho commercial, industrial,
irrigation
 California industrial
Figure 3-11 shows the willingness-to-adopt curves for residential, commercial, and industrial sectors assuming an average
propensity to adopt (the “Mid” case). There was too little irrigation adoption to assess the sector independently, so we used
the commercial curves for the irrigation sector. The right-hand chart in Figure 3-11 shows the high, mid, and low adoption
curves for the residential sector only. The high and low curves for the other sectors show similar variation.

18 Sigrin, Ben and Easan Drury. 2014. Diffusion into New Markets: Economic Returns Required by Households to Adopt Rooftop Photovoltaics. Energy Market Prediction: Papers from the 2014 AAAI Fall Symposium

DNV – www.dnv.com February 2, 2023 Page 8

Figure 3-11 Willingness to Adopt Based on Technology Payback
Willingness to adopt by sector, average propensity to
adopt
Residential willingness to adopt, high-low-mid curves

The willingness-to-adopt curves established a different m parameter for each diffusion curve. In addition to varying by
technology, state, and sector, m also changed over time due to changing payback resulting from changing technology costs,
incentives, and tax credits, among other economic factors).
The timing of our modeled adoption also varied, as we set t0 for each diffusion curve based on the earliest adoption of each
technology by state and sector. For example, the first residential PV installed in PacifiCorp’s Oregon service territory was in
2000, while the first commercial PV installation in its Idaho service territory wasn’t until 2010. For technology/state/sectors
where there is currently no adoption, we assumed that the first adoption would occur in 2023.
The p and q parameters of the Bass diffusion curves were calibrated so that the predicted cumulative adoption from t0
through 2021 was equal to the current market penetration of each technology by state and sector (we fixed the relationship
between p and q at q = 10p to make it possible to solve for p). For technology/state/sectors where there is currently no
adoption, we assumed average values for p and q.
The result of this process were Bass diffusion curves customized for each technology, state, and sector that also accounted
for variation in willingness-to-adopt as cost effectiveness changes over time. The calibrated curves show some segments
still in the very early phases of adoption, while other markets are more mature. Our forecast of annual adoption reflects all of
these differences.

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DNV – www.dnv.com February 2, 2023 Page 9

4 RESULTS
In the base case scenario, DNV estimates 3,181 MW of new private generation capacity will be installed in PacifiCorp’s
service territory over the nest twenty years (2023-2042). Figure 4-1 shows the relationship between the base case and low
and high case scenarios. The low case scenario estimates 2,028 MW of new capacity over the 20-year forecast period—
compared to base case, retail rates increase at a slower rate and technology costs decrease at a slower rate. In the high
case, retail rates increase at a faster rate and technology costs decrease at a faster rate—this results in 3,196 MW of new
private generation capacity installed by 2042.
Table 4-1 Cumulative Adopted Private Generation Capacity by 2042, by Scenario
SCENARIO CUMULATIVE CAPACITY
(2042 MW-AC)
Base 3,181
Low 2,028
High 3,196

Figure 4-1 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), 2023-2042

The sensitivity analysis showed a much greater margin of uncertainty on the low side than the high side. The Inflation
Reduction Act of 2022 (IRA) extends tax credits that for private generation that create very favorable economics for
adoption, and those are embedded in the base case. We therefore limited our upper bound forecast to lower technology
costs and higher retail electricity rates, and these produced only a small boost to adoption for technologies that were already
cost effective under the IRA. In contrast, when we modelled our lower bound, we found that the decreases in cost
effectiveness were enough to tamp down adoption. The low case assumed higher technology costs and lower retail
electricity rates than the other cases, reducing the economic appeal of private generation despite incentives being
unchanged. The low case forecast is 36% less than the base case, while the high case cumulative installed capacity
forecasted over the 20-year period is just 0.5% greater than the base case.
0
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Figure 4-2 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Base Case

Figure 4-3 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, Low Case

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DNV – www.dnv.com February 2, 2023 Page 11

Figure 4-4 Cumulative New Capacity Installed by Technology (MW-AC), 2023-2042, High Case

4.1 Generation Capacity Results by State
The following sections present the results by state for each forecast scenario. Additional exhibits for total PV capacity
forecasted are provided by sector. PV Only and PV + Battery capacity make up at least 95% of each states’ projected
private generation capacity, so providing results for the other technologies by sector would not provide useful context to the
results. The full set of results by state, sector, and new/existing construction for the forecasts is provided in Appendix B.
Figure 4-5 shows the base case forecast by state, compared to the previous (2020) study’s total base case forecast19. This
figure indicates that Utah and Oregon will drive most PG installations over the next two decades, which is to be expected
given these two states represent the largest share of PacifiCorp’s customers and sales. The base scenario estimates
approximately 1,447 MW of new capacity will be installed over the next 10 years in PacifiCorp’s territory—55% of which is in
Utah, 32% in Oregon, and 6% in Idaho. Since the 2020 study, the federal Investment Tax Credit (ITC) has been extended
for ten years at its original base rate levels and expanded to include energy storage. The tax credit increase and extension
lowered the customer payback period for all technologies, making the customer economics of this study’s base case more
similar to the previous study’s high case. In addition to the change in customer economics, projected PV capacity is
expected to grow at a faster rate in the early years and at a slower rate towards the end of the forecast period. The key
drivers of these differences include larger average PV system sizes, decreases in PV + Battery costs, and the maturity of
rooftop PV technology. The adoption model DNV developed for this study was calibrated to existing levels of technology
adoption for each state and sector. Technology adoption follow an S-curve with adoption initially increasing at an increasing
rate, but eventually passing an inflection point where adoption continues to increase at a decreasing rate.

19 Cumulative capacity is adjusted to account for the difference in the forecast starting years (2021 in the previous study, versus 2023 in this study). Source: Navigant. 2020. “Private Generation Long-Term Resource Assessment (2021-2040)”
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Figure 4-5 Cumulative New Capacity Installed by State (MW-AC), 2023-2042, Base Case

4.1.1 California
Customers in PacifiCorp’s service territory in northern California are projected to install about 57 MW of new private
generation capacity over the next two decades in the base case. The 20-year high projection is about 1% greater than the
base case and the low projection is 24% less than the base case, or 57.4 MW and 43 MW, respectively.
California does not currently have any state incentives available for private generation, and uses a net billing structure for
DER compensation. The residential sector has the largest share of the private generation capacity, ranging from 59% in the
low case to 67% in the high and base cases. The next largest share of the capacity is forecasted in the commercial sector,
ranging from 31% in the low case to 24% in the base and high cases.
Figure 4-6 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), California, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 13

Figure 4-7 Cumulative New Capacity Installed by Technology (MW-AC), California Base Case, 2023-2042

Figure 4-8 Cumulative New Capacity Installed by Technology (MW-AC), California Low Case, 2023-2042

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Figure 4-9 Cumulative New Capacity Installed by Technology (MW-AC), California High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 15

4.1.1.1 California PV Adoption by Sector
The impact of the three different scenarios on PV adoption by sector is shown in the following charts, which present the
differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors. In the
residential sector, the share of PV + Battery capacity is about 8% of total PV capacity in 2042 for the high case. The share of
PV + Battery capacity is about 20% of total commercial PV capacity in 2042 for the high case. The irrigation sector has a
similar portion of its PV capacity in PV + Battery configurations, at 14% of total capacity in the high case. The industrial
sector did not have any PV + Battery adoption forecasted.
Figure 4-10 Cumulative New PV Capacity Installed by Sector Across All Scenarios, California, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
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DNV – www.dnv.com February 2, 2023 Page 16

4.1.2 Idaho
PacifiCorp’s customers in Idaho are projected to install about 179 MW of new private generation capacity over the next two
decades in the base case. The 20-year high projection is about 1% greater than the base case and the low projection is 33%
less than the base case, or 181 MW and 121 MW, respectively.
Idaho has a fairly generous incentive program for residential customers that boosted the sector’s adoption, compared to the
other sectors. The incentives are provided through the Residential Alternative Energy Income Tax Deduction, discussed in
section 3.2.5. DNV assumed Idaho would use the same net billing structure for DER compensation as Utah for the study
period (2023-2042). The residential sector has the largest share of the private generation capacity, ranging from 54% in the
base and high cases to 48% in the low case. The next largest share of the capacity is forecasted in the commercial sector,
ranging from 38% in the low case to 34% in the base and high cases.
Figure 4-11 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Idaho, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 17

Figure 4-12 Cumulative New Capacity Installed by Technology (MW-AC), Idaho Base Case, 2023-2042

Figure 4-13 Cumulative New Capacity Installed by Technology (MW-AC), Idaho Low Case, 2023-2042

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Figure 4-14 Cumulative New Capacity Installed by Technology (MW-AC), Idaho High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 19

4.1.2.1 Idaho PV Adoption by Sector
The differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors are
presented in the following charts. In the residential sector, the high case share of PV + Battery capacity is about 15% of total
residential PV capacity in 2042. The share of PV + Battery capacity is about 8% of total commercial PV capacity in 2042.
The irrigation sector has a slightly higher portion of its PV capacity in PV + Battery configurations, at 4% of total capacity.
The industrial sector did not have any PV + Battery adoption forecasted.
Figure 4-15 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Idaho, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
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DNV – www.dnv.com February 2, 2023 Page 20

4.1.3 Oregon
PacifiCorp’s customers in Oregon are projected to install about 1,020 MW of new private generation capacity over the next
two decades in the base case. The 20-year high projection is slightly higher than the base case and the low projection is
39% less than the base case, or 1,022 MW and 623 MW, respectively.
Oregon has incentives available through the Oregon Department of Energy (DOE) for PV + Battery systems and the Energy
Trust of Oregon (ETO) for PV Only configurations. The ETO offers incentives for both residential and business customers,
while the Oregon DOE provides incentives for residential customers only. Both the Oregon DOE and ETO provide increased
incentives for households with low- to moderate-incomes. Oregon is the only state in PacifiCorp’s territory, at this time, that
provides different incentives for residential customers by income level. As the residential private generation forecast was not
segmented by income level, DNV had to develop a single incentive value for the economic analysis. In order to incorporate
the higher incentives for the income-qualified customers, DNV developed a weighted average incentive for Oregon
residential customers. The income-level weights were calculated from the demographic data of the pool of potential adopters
for each technology, in order to best represent the total technology cost (net of incentives) that Oregon residential customers
are making their purchasing decisions based off of. Annual household income was included in the census-tract-level
demographic data that DNV incorporated into PacifiCorp’s Oregon Distribution System Plan circuit-level private generation
forecast. While the higher incentive for income-qualified customers provides a boost to customer economics, it does not
address the other larger barriers to adoption, such as lack of access to capital and home ownership status. Therefore
representation of low- to moderate-income households in the pool of potential adopters for the PV and PV + Battery
technologies is still very low.
The PV + Battery incentives offered for residential customers by the Oregon DOE provided a boost to customer economics
that led to the majority of PV + Battery adoption growth being in the residential sector. The majority of the PV Only adoption
growth in the early years of the forecast is in the commercial sector, with the residential sector following closely behind and
eventually overtaking the forecast in the later years. Oregon’s net metering policies were assumed to stay in place
throughout the study, providing more favorable economics for PV Only—compared to PV + Battery systems.
Figure 4-16 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Oregon, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 21

Figure 4-17 Cumulative New Capacity Installed by Technology (MW-AC), Oregon Base Case, 2023-2042

Figure 4-18 Cumulative New Capacity Installed by Technology (MW-AC), Oregon Low Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 22

Figure 4-19 Cumulative New Capacity Installed by Technology (MW-AC), Oregon High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 23

4.1.3.1 Oregon PV Adoption by Sector
The differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors are
presented in the following charts. In the residential sector, the share of PV + Battery capacity is about 4% of total residential
PV capacity in 2042. The share of PV + Battery capacity is about 2% of total commercial PV capacity in 2042. The irrigation
sector has a similar portion of its PV capacity in PV + Battery configurations, at 3% of total capacity. The industrial sector did
not have any PV + Battery adoption forecasted.
Figure 4-20 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Oregon, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
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4.1.4 Utah
PacifiCorp’s customers in Utah are projected to install about 1,733 MW of new private generation capacity over the next two
decades in the base case. The 20-year high projection is less than 1% greater than the base case and the low projection is
34% less than the base case, or 1,742 MW and 1,140 MW, respectively.
Utah has an incentive program for residential and business customers, but the residential PV incentive expires in 2023. The
incentives are provided through through Utah Office of Energy Development Renewable Energy Systems Tax Credit,
discussed in section 3.2.5. DNV assumed Utah’s net billing policies would remain in place throughout the study. In all cases,
the commercial sector has the largest share of the private generation capacity forecasted—ranging from 50% to 58% in the
high and low cases, respectively. The residential sector represents the 42% of the capacity forecast in the high and base
scenarios, but only 33% in the low case.
Figure 4-21 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Utah, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 25

Figure 4-22 Cumulative New Capacity Installed by Technology (MW-AC), Utah Base Case, 2023-2042

Figure 4-23 Cumulative New Capacity Installed by Technology (MW-AC), Utah Low Case, 2023-2042

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Figure 4-24 Cumulative New Capacity Installed by Technology (MW-AC), Utah High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 27

4.1.4.1 Utah PV Adoption by Sector
The differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors are
presented in the following charts. In the residential sector, the share of PV + Battery capacity is between 28 and 32% of total
residential PV capacity in 2042. The share of PV + Battery capacity is about 4% of total commercial PV capacity in 2042.
The industrial sector has a lower portion of its PV capacity in PV + Battery configurations, at 1% of total capacity. About 5%
of the irrigation sector PV capacity forecasted in in a PV + Battery configuration.
Figure 4-25 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Utah, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
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DNV – www.dnv.com February 2, 2023 Page 28

4.1.5 Washington
PacifiCorp’s customers in Washington are projected to install about 140 MW of new private generation capacity over the
next two decades in the base case. The 20-year low projection is about 47% less than the base case, or 74 MW. The high
case is nearly the same as the base case, seen in Figure 4-26.
Washington state currently offers no incentives for private generation technologies. The residential sector has the largest
share of the private generation capacity, ranging from 68% in the base and high cases to 55% in the low case. The next
largest share of the capacity is forecasted in the commercial sector, ranging from 41% in the low case to 29% in the base
and high cases. Washington’s net metering policies were assumed to stay in place throughout the study, providing more
favorable economics for PV Only—compared to PV + Battery systems.
Figure 4-26 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Washington, 2023-2042

Figure 4-27 Cumulative New Capacity Installed by Technology (MW-AC), Washington Base Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 29

Figure 4-28 Cumulative New Capacity Installed by Technology (MW-AC), Washington Low Case, 2023-2042

Figure 4-29 Cumulative New Capacity Installed by Technology (MW-AC), Washington High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 30

4.1.5.1 Washington PV Adoption by Sector
The differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors are
presented in the following charts. In the residential sector, the share of PV + Battery capacity is about 4% of total residential
PV capacity in 2042. The share of PV + Battery capacity is about 3% of total commercial PV capacity in 2042. The industrial
sector has a higher portion of its PV capacity in PV + Battery configurations, at 8% of total capacity. In the irrigation sector,
the share of PV + Battery capacity is between 2% and 4%, depending on the forecast scenario, of total irrigation PV capacity
in 2042.
Figure 4-30 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Washington, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
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4.1.6 Wyoming
PacifiCorp’s customers in Wyoming are projected to install about 51 MW of new private generation capacity over the next
two decades in the base case. The 20-year high projection is approximately 2% greater than the base case and the low
projection is about 50% less than the base case, or 52 MW and 26 MW, respectively.
Wyoming currently offers no incentives for private generation technologies. The residential sector has the largest share of
the private generation capacity, ranging from 64% in the low case to 71% in the high and bae cases. The next largest share
of the capacity is forecasted in the commercial sector, ranging from 28% in the high and base cases to 34% in the low case.
Wyoming’s net metering policies were assumed to stay in place throughout the study, providing more favorable economics
for PV Only—compared to PV + Battery systems.
Figure 4-31 Cumulative New Private Generation Capacity Installed by Scenario (MW-AC), Wyoming, 2023-2042

Figure 4-32 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming Base Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 32

Figure 4-33 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming Low Case, 2023-2042

Figure 4-34 Cumulative New Capacity Installed by Technology (MW-AC), Wyoming High Case, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 33

4.1.6.1 Wyoming PV Adoption by Sector
The differences in PV capacity relative to the base case for the three modeled scenarios across the four sectors are
presented in the following charts. In the residential sector, the share of PV + Battery capacity is between 19% and 23% of
total residential PV capacity in 2042, depending on the forecast scenario. The share of PV + Battery capacity is about 6% of
total commercial PV capacity in 2042. The industrial sector has a lower portion of its PV capacity in PV + Battery
configurations, at 5% of total capacity. The irrigation sector did not have any PV (PV Only or PV + Battery) adoption
forecasted.
Figure 4-35 Cumulative New PV Capacity Installed by Sector Across All Scenarios, Wyoming, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
Residential Commercial
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APPENDIX A TECHNOLOGY ASSUMPTIONS AND INPUTS
Appendix A.xlsx

DNV – www.dnv.com February 2, 2023 Page 35

APPENDIX B DETAILED RESULTS
Appendix B.xlsx

DNV – www.dnv.com February 2, 2023 Page 36

APPENDIX C WASHINGTON COGENERATION LEVELIZED COSTS
Section 480.109.100 of the Washington Administrative Code 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. This appendix provides the levelized cost of energy (LCOE)
for the two CHP technologies analyzed in this report for three 10-year periods. LCOE is defined as the present cost of
electricity generation for the specified technology over its useful lifetime.
Assumptions for the LCOE analysis of both reciprocating engines and microturbines in Washington state are provided in
Table C-1and Table C-2 below, with additional information on the specific source for each metric. Similar to previous studies,
the cost of system heat recovery was removed from the total system cost component, resulting in LCOE based only on
electric power generation for each system. Where applicable, assumptions are presented nominally ($USD).
Table C-1 Reciprocating Engine LCOE Assumptions
METRIC EXPECTED USEFUL
LIFE (EUL)
INSTALLED COST
(INCLUDES INCENTIVES)
VARIABLE O&M
COST
FUEL COST WACC
UNITS Years $/kW $/MWh $/MMBtu %
2022 20 $2,565 $23 $5.67 6.88%
2030 20 $2,655 $27 $4.34 6.88%
2040 20 $2,721 $32 $6.61 6.88%
SOURCE EPA Catalog of CHP
Technologies (Sep.
2017)
DOE CHP Technology
Fact Sheets
(Reciprocating Engines)
DOE CHP Technology
Fact Sheets
(Reciprocating Engines)
PacifiCorp Natural Gas
Forecast for Washington
State
PacifiCorp IRP
Assumption

Table C-2 Microturbine Engine LCOE Assumptions
METRIC EXPECTED USEFUL
LIFE (EUL)
INSTALLED COST
(INCLUDES INCENTIVES)
VARIABLE O&M
COST
FUEL COST WACC
UNITS Years $/kW $/MWh $/MMBtu %
2022 25 $3,135 $23 $5.67 6.88%
2030 25 $3,229 $27 $4.34 6.88%
2040 25 $3,294 $32 $6.61 6.88%
SOURCE EPA Catalog of CHP
Technologies (Sep.
2017)
DOE CHP Technology
Fact Sheets
(Reciprocating Engines)
DOE CHP Technology
Fact Sheets
(Reciprocating Engines)
PacifiCorp Natural Gas
Forecast for Washington
State
PacifiCorp IRP
Assumption

DNV – www.dnv.com February 2, 2023 Page 37

The results of the CHP LCOE analysis are shown below. The calculated levelized costs for both technologies are similar in each analysis year.
Table C-3 LCOE Results for CHP Systems in Washington State
TECH RECIPROCATING
ENGINES
MICROTURBINES
UNITS $/MWh $/MWh
2022 $89.3 $92.8
2030 $99.4 $99.9
2040 $121.4 $116.3

DNV – www.dnv.com February 2, 2023 Page 38

APPENDIX D OREGON DISTRIBUTION SYSTEM PLAN RESULTS
DNV prepared the Long-Term Private Generation (PG) Resource Assessment for PacifiCorp’s Oregon distributed energy
resource (DER) adoption forecast at the circuit level to support PacifiCorp’s 2023 Oregon Distribution System Plan (DSP).
This study evaluated the expected adoption of behind-the-meter DERs including photovoltaic solar (PV only), photovoltaic
solar coupled with battery storage (PV + Battery), wind, small hydro, reciprocating engines and microturbines for a 20-year
forecast horizon (2023-2042). The adoption model DNV developed for this study is calibrated to the current20 market
penetration of these technologies, shown in Figure D-1.
Figure D-1 Historic Cumulative Installed PG Capacity by Technology, PacifiCorp, Oregon, 2012-2021

To date, about 99 percent of existing private generation capacity installed in PacifiCorp’s Oregon service territory is PV or
PV + Battery. To inform the adoption forecast process, the Company conducted an in-depth review of the other technologies
and did not find any literature to suggest that they would take on a larger share of the private generation market in Oregon in
the future years of this study.
For each technology and sector, PacifiCorp developed three scenarios: a base case, a high case and a low case. The base
case is considered the most likely projection as it is based on current market trends and expected changes in costs and
retail rates; the high and low cases are used as sensitivities to test how changes in technology costs and retail rates impact
customer adoption of these technologies. These scenarios use technology cost and performance assumptions specific to
PacifiCorp’s Oregon service territory in the base year of the study. The base case assumes the current federal income tax
credit schedules and state incentives, retail electricity rate escalation from the AEO21 reference case, and a blended version
of the NREL Annual Technology Baseline22 moderate and conservative technology cost forecasts. In the high case, retail
rates increase more rapidly, and technology costs decline at a faster rate compared to the base case to incentivize greater
adoption of PG. For the low case, retail rates increase at a slower rate than the base case and technology costs decrease at
a slower rate.

20 PacifiCorp private generation interconnection data as of February 2022.
21 U.S. Energy Information Administration, Annual Energy Outlook 2022 (AEO2022), (Washington, DC, March 2022).
22NREL (National Renewable Energy Laboratory). 2021. 2021 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory.
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DNV – www.dnv.com February 2, 2023 Page 39

D.1 Study Methodologies and Approaches
The forecasting methodologies and techniques applied by PacifiCorp in this analysis are commonly used in small-scale,
behind-the-meter energy resource and energy efficiency forecasting. To forecast private generation adoption at the circuit-
level, the Company first developed an adoption model to estimate total PG potential for PacifiCorp’s Oregon service territory
and then disaggregated these results to develop PG potential estimates for each circuit. The methods used to develop the
territory and circuit level results are described in more detail below.
D.1.1 State-Level Forecast Approach
DNV developed a behind-the-meter net economic perspective that includes the acquisition and installation costs for each
technology and incorporates the available incentives and economic benefits of ownership as offsets which assumed that the
current net metering policies for Oregon remained in place throughout the study horizon. The economic analysis calculated
payback by year for each technology by sector. A corresponding technical feasibility analysis determined the maximum,
feasible, adoption for each technology by sector. The results of the technical and economic analyses were then used to
inform the market adoption analysis. The methodology and major inputs to the analysis are shown in Figure D-2. Changes to
technology costs, retail rates, and federal tax credits used in the high and low cases impact the economic portion of the
analysis.
Figure D-2 Methodology to Determine Market Potential of Private Generation Adoption

PacifiCorp used technology and sector-specific Bass diffusion curves to model market adoption and derive total market
potential. Bass diffusion curves are widely used for forecasting technology adoption. Diffusion curves typically take the form
of an S-curve with an initial period of slow early adoption, adoption increasing as the technology becomes more mainstream,
and eventually a tapering off among late adopters. The upper limit of the curve is set to maximum market potential, or the
maximum share of the market that will adopt the technology regardless of the interventions applied to influence adoption. In
this analysis, the long-term maximum level of market adoption was based on payback. As payback was calculated by year in
the economic analysis to capture the changing effects of market interventions over time, the maximum level of market
adoption in the diffusion curves vary by year in the study.
The model is characterized by three parameters—an innovation coefficient, an imitation coefficient, and the ultimate market
potential. The last of these we set equal to the payback-based maximum level of adoption. Together, these three
parameters also determine the time to reach maximum adoption and overall shape of the curve. The innovation and
Market Potential
Economic Analysis
Technology costs
Installation and O&M costs
Local and federal incentives
Benefits of ownership
Energy savings
Net billing, net metering export credits
Technical Feasibility
System performance constraints
Customer load shapes
System size limits
Land-use requirements
Non-shaded rooftop space
Access to unprotected streams and dams, wind resource

DNV – www.dnv.com February 2, 2023 Page 40

imitation parameters were calibrated for each technology and sector, based on current market penetration and when
PacifiCorp started to see the technology being adopted in the Company’s Oregon service territory.
D.1.2 Circuit-Level Forecasting Approach
PacifiCorp conducted a bottom-up approach to develop circuit-level adoption models for each sector and technology. The
approach chosen for developing circuit-level forecasts was to disaggregate the state-level forecast described in the previous
section. This was due to the use of adoption drivers from data at varying levels of geographic granularity. The circuit-level
adoption models incorporated county-level private generation installation data and resource availability by technology23,
census-tract-level demographic data24 and circuit-level reliability data. The Company used circuit-level customer counts by
sector to further segment the localized adoption models by sector and technology. The Company ultimately used a bottom-
up approach to develop circuit-level adoption models for each circuit, but due to the above data gaps, their purpose was only
to develop factors to allocate the state-wide analysis to each circuit.
D.2 Private Generation Forecast Results
Figure D-3 compares the new service territory-level private generation capacity, in cumulative MW-AC by 2033, projected for
each scenario evaluated. The capacity forecasted is incremental to what is already installed in PacifiCorp’s Oregon service
territory, shown in Figure D-1.
Figure D-3 Private Generation Forecast by Technology, PacifiCorp Oregon, All Cases

Similar to the trends observed in current installed capacity, solar PV25 makes up 99% of the new PG capacity forecast
throughout the study period in all cases. By 2033, the cumulative new PV Only capacity in the base case is 209 MW and PV
+ Battery capacity is 5 MW. Compared to the base case, the low case forecasts 31% less PV Only capacity, and about 40%
percent less PV + Battery capacity. The PV Only cumulative new capacity in the high case in 2033 is 83% greater than the
base case. In the high case, 2033 PV + Battery cumulative new capacity is forecasted to be more than double the base
case, at 11 MW.

23 Conditions suitable for wind and hydro vary widely by region, and the economics of solar adoption is affected by local weather patterns.
24 Data including household income, education-level, and home ownership.
25 The term solar PV, here, is inclusive of PV Only and PV + Battery systems.
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2033 Cumulative New Capacity Installed: 148 MW-AC

DNV – www.dnv.com February 2, 2023 Page 41

D.2.1 Circuit-Level and Substation-Level Results Findings
The charts in Figure D-4, Figure D-5, and Figure D-6 show the distribution of new capacity in 2033 by operating area,
substation, and circuit within the base case private generation forecast.
Figure D-4 Private Generation Forecast Disaggregation by Operating Area, PacifiCorp Oregon, Base Case

The top five (ranked by new capacity) of PacifiCorp’s 22 Oregon operating areas account for 65% of the total forecast
capacity in 2033 while only accounting for 48% of total customers.
Figure D-5 Private Generation Forecast Disaggregation by Substation, PacifiCorp Oregon, Base Case

The top five of PacifiCorp’s 193 substations account for 15% of 2033 forecast capacity (compared to 7% of customers), with
the entire top quartile (representing 49% of customers) accounting for 67%.
Second quartile, 23%
Third quartile, 8%
Bottom Quartile, 4%
Medford, 22%
Bend/Redmond, 19%
Klamath Falls, 12%
Portland, 6%
Madras, 6%
Top quartile65%
Distribution of New Capacity (2033) by Operating Area
The top 5 operating areas account for 48%
of total customers
Rest of Top Quartile52%
Second quartile21%
Third quartile10%Bottom Quartile2%Redmond, 4%
Cleveland Ave., 4%
Prineville, 3%
Medford, 2%
Hood River, 2%
Top 5 substations15%
Distribution of New Capacity (2033) by Substation
The top 5 substations account for 7.1%
of total customers

DNV – www.dnv.com February 2, 2023 Page 42

Figure D-6 Private Generation Forecast Disaggregation by Circuit, PacifiCorp Oregon, Base Case

Of the 504 circuits analyzed, the top five (representing 2.6% of customers) account for 5.2% of total forecast capacity, with
the top quartile (representing 36% of customers) accounts for 59%.
Figure D-7 shows the breakdown of customers, by sector, at the top five substations. Because capacity sizes are larger for
irrigation, commercial and industrial customers than for residential (four times larger for irrigation, nine times for commercial
and 17 times for industrial), C&I customers contribute to capacity totals disproportionately to their share of the customer
population. New construction has a two-fold impact on the capacity forecast: Directly, since there are customers on the
substation who could adopt private generation, and indirectly, since new construction has a higher propensity to adopt solar
(with and without storage) than existing buildings. All substations except Hood River are in areas where population growth is
higher than the statewide average.
Figure D-7 Customer Mix of Top Five Substations Compared to the Average of All Substations

Rest of Top Quartile, 54.1%
Second Quartile, 26.9%Third Quartile, 11.6%
Bottom Quartile, 2.2%5D167, 0.8%
5D411, 1.0%
5D94, 1.1%
5D227, 1.1%
4M16, 1.2%
Top 5 Circuits5.2%
Distribution of New Capacity (2033) by Circuit
The top 5 circuits account for 2.6%of
total customers
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With 193 substations across the state and so many factors influencing the disaggregated forecast, it is not feasible to
conduct a deep dive of each substation’s capacity forecast. Instead, we selected five substations to illustrate how different
underlying factors affected their capacity allocations (see Figure D-8). These substations were chosen to illustrate a range of
characteristics influencing adoption, not because they are of special interest for planning.
Figure D-8 Customer Attributes of Selected Substations Compared to Average PacifiCorp Oregon Substation
Substation
Attribute Vernon Cleveland
Ave. Mary's River Coquille Vilas Road Average
Operating Area Portland Bed/
Redmond Corvallis Coos
Bay/Coquille Medford --
Climate (for Solar) Less
favorable
More
favorable
Less
favorable
Less
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More
favorable --
Population Growth 1.0% 2.0% 1.3% 0.0% 1.7% 1.0%
% Non-res.
Customers 5% 20% 12% 13% 34% 16%
Current Res. Solar
Penetration 1.4% 3.0% 3.1% 0.9% 2.4% 1.8%
Home Ownership
Rate 70% 55% 61% 77% 75% 65%
Avg. Household
Income $108,604 $136,460 $102,301 $74,543 $58,752 $87,499

Vernon and Cleveland Avenue are among PacifiCorp’s top substations by number of customers but have very different
climates and customer mixes. Cleveland Avenue lies on the east side of the Cascades and receives more sunshine, while
Vernon is in the Portland operating area, which has more rain and more cloudy days which impacts solar generation and
thus adoption. Nonresidential PV systems are larger than residential systems (modeled commercial systems are 9 times
larger; industrial systems are 17 times larger), so Cleveland Ave’s higher share of nonresidential customers (20%) increases
its capacity forecast compared to Vernon, with only 5% nonresidential customers. Cleveland Avenue also has double the
rate of expected population growth that Vernon does over the next decade.
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The remaining three substations shown each have a total customer count close to the state-wide average, but very different
capacity forecasts. Mary’s River has high historic adoption and higher-than-average population growth, but less non-
residential and a lower home ownership rate than average resulted in a share of capacity almost proportional to the number
of customers. Coquille has very low historic adoption, perhaps due to its less favorable climate for solar generation, and no
expected population growth. Those factors, paired with lower-than-average income and low share of non-residential
customers led to a very low level of forecast private generation capacity. The last substation we wish to highlight is Vilas
Road in the Medford operating Area. This substation has a very high share of non-residential customers at 34%, and the
higher capacity systems for these customers drives up the forecast. A favorable climate for solar with high historic adoption
(residential and commercial) led to this substation being allocated a higher-than-proportional share of capacity.
Figure D-9 zooms in on the Klamath Falls operating area to compare how the allocation of PV only capacity compares to the
distribution of customers by circuit. For each circuit in the Klamath Falls operating area, the chart shows the share of
residential customers to the corresponding share of the 2033 residential PV Only capacity forecast. The figure demonstrates
visually that more favorable factors for adoption, such as higher rates of home ownership, higher income, higher education,
etc. result in a higher than proportional allocation of capacity.
Figure D-9 Share of Residential Customers vs. Share of Residential PV Only Capacity in 2033, Klamath Falls
Operating Area

D.3 Conclusions
As part of the DSP, PacifiCorp evaluated each of the previously discussed private generation scenarios. However, as the
baseline DSP private generation forecast, PacifiCorp considers the base case forecast to be most appropriate for planning,
given current technology costs, incentive levels and net metering policies in place in Oregon.
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-Median Income: $50,035-% Owner Occupied: 69%-% w/ Bachelor's Degree: 27%
-Median Income: $32,879-% Owner Occupied: 38%-% w/ Bachelor's Degree: 16%
Circuit 5L45

DNV – www.dnv.com February 2, 2023 Page 45

Our analysis incorporated the current rate structures and tariffs offered to customers in Oregon. Time-of-use rates, tiered
tariffs and retail tariffs that include high demand charges increased the value of PV + Battery configurations compared to
PV-Only configurations while other factors such as load profiles and DER compensation mechanisms minimized the impact
of such tariffs on the customer economics of PV + Battery systems. The DER compensation mechanism in Oregon —
traditional net metering — does not incentivize PV + Battery storage co-adoption.
The sensitivity analysis found a greater difference between the base case and the upper bound of private generation
adoption than the base case and lower bound of adoption. The low case assumed higher technology costs and lower retail
electricity rates than the other cases, reducing the economic appeal of private generation despite incentives being
unchanged. For the high case, an assumed extension to the residential federal investment tax credit provided a significant
boost to adoption alongside the lower technology costs and higher retail electricity rates used in that analysis. The resulting
new capacity in 2033 is about 31% less than the base case, while the high case is 84% greater than the base.
D.3.1 Future Work
Developing the circuit-level adoption models within the Oregon adoption model revealed additional areas of research related
to private generation and behind-the-meter battery storage adoption that would enhance future work. The following is a list
of potential future enhancements to this study:
1. A more nuanced approach to the new construction forecast would consider the creation of new circuits in high-
growth areas. The current study allocates new construction only to existing circuits.
2. The distribution analysis requires integrating data at different geographical resolutions (state, county, census tract
and circuit). While PacifiCorp’s data mapped circuits geographically, there were challenges in matching customer
billing data to circuits. This study also used existing customer counts by sector by circuit, but corresponding energy
use could not be calculated at the circuit-level. Similarly, existing private generation could only be mapped at the
county level since interconnection data had incomplete customer circuit information. Future studies will benefit from
the circuit-level load forecasts PacifiCorp is developing for this DSP.
3. Storage dispatch modeling would benefit from a finer disaggregation of large commercial and industrial load
shapes. Technology that is not broadly cost-effective could still be beneficial for customers with certain load profiles
that were not visible using class-level load shapes.
4. Resilience appeared to be a significant driver of adoption. For PV + Battery storage, resilience could be a more
significant driver of adoption than economics. A deeper understanding of what customer-types value resilience and
how that affects their willingness to pay would help refine the forecast.

DNV – www.dnv.com February 2, 2023 Page 46

APPENDIX E BEHIND-THE-METER BATTERY STORAGE FORECAST
DNV prepared a behind-the-meter battery storage forecast as a part of the Long-Term Private Generation (PG) Resource
Assessment for PacifiCorp covering their service territories in Utah, Oregon, Idaho, Wyoming, California, and Washington to
support PacifiCorp’s 2023 Integrated Resource Plan (IRP). This study evaluated the expected adoption of behind-the-meter
battery storage systems coupled with PV systems over a 20-year forecast horizon (2023-2042) for all customer sectors
(residential, commercial, industrial, and agricultural). Residential and non-residential battery energy storage systems (BESS)
can be installed as a standalone system, added to an existing PV system, or the system can be installed together with a new
PV system. DNV assumed all battery installations would be paired with a PV system in an AC-coupled configuration, as
standalone systems are ineligible for the federal ITC—explained further in section 3.2.5.
The adoption model DNV developed for this study is calibrated to the current26 installed and interconnected behind-the-
meter battery capacity that is paired with a PV system, shown in Figure E-1.
Figure E-1 Historic Cumulative Installed Behind-the-Meter Battery Storage Capacity, PacifiCorp, 2012-2021
Historic Cumulative Installed Battery Capacity by State Historic Cumulative Installed Battery Capacity
by Sector

E.1 Study Methodologies and Approaches
DNV modelled two technologies in the behind-the-meter battery storage forecast:
1. PV + Battery: BESS product installed together with a new PV system,
2. Battery Retrofit: BESS product installed as an add-on to an existing PV system.

26 PacifiCorp private generation interconnection data as of February 2022.
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DNV used the same forecasting methodologies and approaches for the BTM battery storage forecast as the private
generation forecast. The methods used to develop the results of the forecast are described in detail in section 3.4 of the
report.
Data on battery system costs used in the BTM battery storage forecast is explained in detail in section 3.1.1.2 of the report.
That section includes current and projected future costs of battery storage systems used in the forecast for the different
sectors. The detailed assumptions for the system configurations, including system sizes, in each sector and state can be
found in Appendix A.
E.1.1 Battery Dispatch Modelling
DNV utilized its proprietary solar plus storage operational modeling tool—Lightsaber—to model battery dispatch. Battery
dispatch strategy dictates the flow of energy between the PV system, battery, and the grid. The battery dispatch model
includes strategies such as peak shaving, energy arbitrage, and manual dispatch. Self consumption was modelled for all
sectors’ BESS control strategy, which utilizes the battery by charging only from excess PV and discharging if PV production
falls below load. For residential customers, the dispatch model used energy arbitrage to reduce time-of-use charges. For
non-residential customers, the dispatch model used energy arbitrage to reduce demand charges and time-of-use charges,
where applicable.
E.2 Results
In the base case scenario, DNV estimates 227 MW of new battery storage capacity will be installed in PacifiCorp’s service
territory over the nest twenty years (2023-2042). Figure E-2 shows the relationship between the base case and low and high
case scenario forecasts. The low case scenario estimates 151 MW of new capacity over the 20-year forecast period—
compared to base case, retail rates increase at a slower rate and technology costs decrease at a slower rate. In the high
case, retail rates increase at a faster rate and technology costs decrease at a faster rate—this results in 264 MW of new
private generation capacity installed by 2042. The twenty year total new capacity forecasted in the high case is about 16%
greater than the base case, while the low case is 34% less.
Table E-1 Cumulative Adopted Battery Storage Capacity by 2042, by Scenario
SCENARIO CUMULATIVE CAPACITY
(2042 MW)
Base 227
Low 151
High 264

DNV – www.dnv.com February 2, 2023 Page 48

Figure E-2 Cumulative New Battery Storage Capacity Installed by Scenario (MW), 2023-2042

Figure E-3, Figure E-4, and Figure E-5 show the forecasts by customer sector and technology for each scenario. In all
scenarios of the forecast, the residential sector represents about 90% of the new battery storage capacity forecasted to be
installed over the next twenty years. The commercial, industrial, and irrigation sectors have been bundled into a single “Non-
Residential” sector for the purpose of presenting the results in the report, as the capacity forecasts in the individual sectors
are very small relative to the total forecast. PV + Battery systems represent the greatest share of the new battery capacity
forecasted in the base and high cases. Battery Retrofit systems representing a greater share of the new battery capacity
forecasted in the low case indicates that customers are more likely to adopt a PV Only system over a PV + Battery system
when technology costs are higher and electricity rates are lower.
Figure E-3 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, Base Case

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DNV – www.dnv.com February 2, 2023 Page 49

Figure E-4 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, Low Case

Figure E-5 Cumulative New Battery Storage Capacity Installed by Technology (MW), 2023-2042, High Case

E.3 Storage Capacity Results by State
As was the case in the private generation forecast, Utah represents the largest share of the battery capacity forecast. To
date, the majority of installed battery storage capacity and annual growth in storage capacity has been in Utah, which
represents the largest portion go PacifiCorp’s customer population. Battery adoption is expected to continue to grow in Utah,
with the state’s share of total new capacity reaching between 81% and 84%, depending on the scenario, over the next
twenty years. The net billing structure in place in Utah incentivizes PV + Battery storage co-adoption more so than traditional
net metering, as customers can lower their electricity bills by charging their batteries with excess PV generation and
dispatching their batteries to meet on-site load during times of day when retail energy prices are high. Oregon represents the
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DNV – www.dnv.com February 2, 2023 Page 50

second largest portion of the new capacity forecasted, between 8% and 10%. Net metering is the DER compensation
mechanism in place in Oregon, but customer economics are boosted by PV + Battery incentives provided through the
Oregon Department of Energy27.
Figure E-6 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, Base Case

Figure E-7 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, Low Case

27https://www.oregon.gov/energy/Incentives/Pages/Solar-Storage-Rebate-Program.aspx
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Figure E-8 Cumulative New Battery Storage Capacity Installed by State (MW), 2023-2042, High Case

The following figures show the state-level forecasts in more detail. Background and commentary on the individual states’
results can be found in section 4.1 of the report.
California
Figure E-9 Cumulative New Battery Storage Capacity Installed by Scenario (MW), California, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 52

Figure E-10 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW),
California, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
CA Residential PV + Battery CA Residential Battery Retrofit
CA Non-Residential PV + Battery CA Non-Residential Battery Retrofit

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Idaho
Figure E-11 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Idaho, 2023-2042

Figure E-12 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Idaho,
2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
ID Residential PV + Battery ID Residential Battery Retrofit
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ID Non-Residential PV + Battery ID Non-Residential Battery Retrofit

Oregon
Figure E-13 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Oregon, 2023-2042

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DNV – www.dnv.com February 2, 2023 Page 55

Figure E-14 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Oregon,
2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
OR Residential PV + Battery OR Residential Battery Retrofit
OR Non-Residential PV + Battery OR Non-Residential Battery Retrofit

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Utah
Figure E-15 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Utah, 2023-2042

Figure E-16 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW), Utah,
2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
UT Residential PV + Battery UT Residential Battery Retrofit
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UT Non-Residential PV + Battery UT Non-Residential Battery Retrofit

Washington
Figure E-17 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Washington, 2023-2042

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Figure E-18 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW),
Washington, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
WA Residential PV + Battery WA Residential Battery Retrofit
WA Non-Residential PV + Battery WA Non-Residential Battery Retrofit

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Wyoming
Figure E-19 Cumulative New Battery Storage Capacity Installed by Scenario (MW), Wyoming, 2023-2042

Figure E-20 Cumulative New Battery Storage Capacity Installed by Technology Across All Scenarios (MW),
Wyoming, 2023-2042
Upper and lower bounds (in blue) represent the high and low case forecasts, with a line for the base case.
WY Residential PV + Battery WY Residential Battery Retrofit
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WY Non-Residential PV + Battery WY Non-Residential Battery Retrofit

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About DNV
DNV is a global quality assurance and risk management company. Driven by our purpose of safeguarding life, property and the environment, we enable our customers to advance the safety and sustainability of their business. We provide classification, technical assurance, software and independent expert advisory services to the maritime, oil & gas, power and renewables industries. We also provide certification, supply chain and data management services to customers across a wide range of industries. Operating in more than 100 countries, our experts are dedicated to helping customers make the world safer, smarter and greener.

PACIFICORP – 2023 IRP APPENDIX M – RENEWABLE RESOURCES ASSESSMENT
323

APPENDIX M – RENEWABLE RESOURCES
ASSESSMENT
A study on renewable resources and energy storage was commissioned to support PacifiCorp’s 2023 Integrated Resource Plan (IRP). The “2023 Renewables IRP” Assessment, prepared by WSP is screening-level in nature and includes a comparison of technical capabilities, capital costs, and
operations and maintenance costs that are representative of renewable energy and storage technologies. The WSP Assessment builds upon prior studies, updates cost and technical information and adds gravity energy storage options (other than Pumped Hydro Energy Storage, or PHES) and offshore wind (OSW).
This report compiles the assumptions and methodologies used by WSP during the Assessment. Its purpose is to articulate that the delivered information is in alignment with PacifiCorp’s intent to advance its resource planning initiatives.

PACIFICORP – 2023 IRP APPENDIX P – RENEWABLE RESOURCES ASSESSMENT
324

PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

APPENDIX O – WASHINGTON 2021 IRP TWO-YEAR
PROGRESS REPORT ADDITIONAL
ELEMENTS
Introduction
Washington passed the Clean Energy Transformation Act (CETA) in 2019, which combines
directives for utilities to pursue a clean energy future with assurances that benefits from a transformation to clean power are equitably distributed among all Washingtonians.1 The Washington Utilities and Transportation Commission began rulemakings to implement CETA in June 2019, and the first phase concluded in December 2020. As directed by the legislation and
the new CETA rules, beginning January 1, 2023, the Company must file a two-year progress report at least every two years after PacifiCorp has filed its IRP.2 This two-year progress report must include the following:
- Updated load forecast, demand-side resource assessment, including a new conservation
potential assessment; resource costs; and portfolio analyses and preferred portfolios; - Other updates necessary due to changing state or federal requirements, or significant changes to economic or market forces; and - Update any elements found in the utility’s current clean energy implementation plan
(CEIP).3
The Company’s updated load forecast can be found in Volume 1, Appendix A; demand-side resource assessment and new conservation potential assessment can be found in Chapter 6 and the
Specific Actions section below; resource costs can be found in Volume I, Chapter 7; and relevant
portfolio analyses can be found in Volume I, Chapters 8 and 9, and the Interim and Specific
Targets section below.4 Relevant state and federal policy updates, as well as changes to economic or market forces, can be found in Volume I, Chapter 3.5 Aligned with the refiled CEIP,6 this 2021 IRP Two-Year Progress Report includes updates on the
following CEIP elements: Interim and Specific Targets; Updated Inputs, including portfolio

1 2019 WA Laws Ch. 288.
2 WAC 480-100-625. 3 Id. -625(4).
4 Id. -625(4)(a). 5 Id. -625(4)(b).
6 PacifiCorp filed its first Clean Energy Implementation Plan (CEIP) on December 29, 2021, with the Washington Utilities and Transportation Commission (WUTC) in docket UE-210289. The Company filed a Revised Errata to the
CEIP to make a small correction to a workpaper that resulted in a change in the calculated incremental cost. Consistent with UE-220376, Order 06, the Company refiled its 2021 CEIP on March 13, 2023, and relevant CEIP elements are
included in this 2021 IRP Two-Year Progress Report.
383
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

analysis and preferred portfolios; Customer Benefit Indicators; Specific Actions, including both
supply and demand-side actions; Incremental Costs; Public Participation; and Annual Reporting. Each of these updated CEIP elements are discussed below. Additionally, consistent with WAC 480-100-650, more detailed and specific reporting on CEIP targets, actions, and CBIs will be
included in the Company’s annual clean energy progress report due this summer, and CEIP
biennial update due later this fall.
Interim and Specific Targets CETA’s clean energy transformation requires Washington utilities to eliminate coal-fired resources from its allocation of electricity to Washington retail electric customers by 2026; ensure
all retail sales of electricity to Washington electric customers are greenhouse gas neutral by 2030; and ensure that non-emitting electric generation and electricity from renewable resources supply one hundred percent of all retail sales of electricity to Washington electric customers by 2045.7 Prior to 2045, CETA allows for up to 20 percent of the greenhouse gas neutral standard to be met
with alternative compliance in the form of alternative compliance payments, unbundled RECs, energy transformation projects, or energy recovery from a municipal solid waste facility.8 To achieve the 2045 target, the clean energy standard must be met with 100 percent non-emitting generation or electricity from renewable energy resources. Furthermore, PacifiCorp must demonstrate that it “has made progress toward and has met the standards in this section at the
lowest reasonable cost.”9 Consistent with these requirements and WAC 480-100-640, the Company proposes interim targets to demonstrate its trajectory toward meeting CETA’s decarbonization targets. Updated interim targets are based on data and methodologies consistent with portfolio development and modeling
in Volume 1, Chapters 8 and 9, and with CEIP requirements. Specifically, CEIP targets are demonstrated for a least-cost, least-risk portfolio optimized under the price policy assumption that includes societal cost of greenhouse gas emissions (SCGHG).10 As shown in Volume I, Chapter 8 (Modeling and Portfolio Evaluation), Figure 8.4 – the SCGHG
starts at just over $80/ton in 2023 and reaches about $170/ton in 2042. In addition to the assumed carbon dioxide price, there is an additional forecasted cost of allowances under the cap-and-invest program established in the Climate Commitment Act passed by Washington Legislature in 2021. This forecasted allowance cost is applied to all emissions from the Chehalis natural gas plant located in Washington. The modeled allowance cost reflects analysis conducted by Vivid

7 WAC 480-100-610(1-3).
8 RCW 19.405.040(1)(b). 9 WAC 480-100-610(5).
10 The SCGHG dispatch adder is modeled in both the resource acquisition decision (capacity expansion in the LT model), and in operations (dispatch in the MT and ST models) as described in Volume I, Chapter 8 (Modeling and
Portfolio Evaluation).
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

Economics for the Washington Department of Ecology and starts at $58/ton in 2023.11 For more
discussion of the system-wide portfolio impacts of the SC price-policy assumptions and CETA-related portfolio impacts, see results in Volume I, Chapter 9 (Modeling and Portfolio Selection Results).
Based on these updated portfolio inputs, the Company anticipates supplying 26 percent renewable
and non-emitting energy to serve Washington retail sales in 2023, increasing to 33 percent in 2025, to 82 percent in 2030, and finally over 100 percent beginning in 2032 and maintaining this percentage for the remainder of the Company’s planning period.
Interim Targets
This section includes PacifiCorp’s interim compliance targets for the first CETA action period (2022-2025), and to achieve CETA’s 2030 and 2045 targets.
Figure O.1 reports PacifiCorp’s updated interim targets that are derived from the portfolio denoted W-10 CETA.12 This portfolio was developed to meet CETA’s 2030 and 2045 decarbonization targets under the SCGHG price policy assumption. In the figure interim targets are divided into two forecast ranges: the first focuses on meeting CETA’s 100 percent GHG neutrality standard by
2030, and the second focuses on meeting the 100 percent non-emitting and renewable energy target by 2045. As shown in the figure, the Company expects to have achieved CETA’s ambitious decarbonization targets well over a decade in advance of the 2045 deadline. Post-2030, the last three years to reach the 2045 objective are beyond the Company’s current 20-
year study period. Rather than creating extrapolated and imprecise forecasts for every data point underlying the analysis to extend into 2045, the company has extrapolated the last three years of data based on the already optimized and established trajectory. However, this exercise was unnecessary given that the portfolio shows 100 percent clean energy as a percentage of Washington retail sales by 2032.

11 Washington DOE Summary of market modeling and analysis of the proposed Cap and Invest Program, at 4 (Jun. 2022) (available here: https://ecology.wa.gov/DOE/files/4a/4ab74e30-d365-40f5-9e8f-528caa8610dc.pdf; accessed
Mar. 31, 2023). 12 Several portfolios were developed to analyze the impacts of CETA in various planning scenarios, and are defined
in Volume I, Chapter 8 (Modeling and Portfolio Evaluation).
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

Figure O.1 - Interim Targets
Table O.1 below reports updated interim targets for the Company’s first CEIP action period for years 2022 through 2024, reported as annual megawatt hours of energy rather than as percentages. Since this two-year IRP progress report is forward-looking, portfolio inputs, outputs, and interim targets begin from year 2023. However given the Company’s current CEIP focuses on the CEIP
compliance period from 2022 to 2025, this same compliance period is reflected below. The values for 2022 are from the Company’s March 13, 2023 Refiled CEIP and have not been updated, and are informed by the company’s historical performance under median water conditions, a factor in developing expected resource behaviors and Washington retail sales.
Table O.1 - Interim Compliance Targets (MWh)
20221 2023 2024 2025 Total
Retail Electric Sales 4,051,128 4,128,751 4,141,107 4,106,386 16,427,372
Projected Renewable and
Non-emitting Energy 1,262,111 1,081,277 1,028,236 1,367,667 4,739,291
Net Retail Sales 2,789,017 3,047,474 3,112,871 2,738,719 11,688,081
Target Percentage 31% 26% 25% 33%
Interim Compliance
Target 1,262,111 1,081,277 1,028,236 1,367,667 4,739,291
1 Originally estimated target for 2022 based on Refiled 2021 CEIP, March 13, 2023 These updated interim targets reflect both updates from the Company’s portfolio results, as well as updated resource allocation assumptions. Importantly, increases in system load, changes in
price curves and fuel inputs, and development in federal regulation like the Ozone Transport
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

Rule, have driven significant growth in system renewable resources across the planning horizon.
However, ongoing wholesale energy market volatility has forced the Company to consider options to mitigate increasing net power costs that adversely affect PacifiCorp’s near-term CETA targets. Compliance with CETA continues to be supported by the IRP with the addition of non-emitting system resources. Ongoing negotiations in MSP, updated REC assumptions, and a
realignment of assumptions about uncertain future Washington resource allocations have all led
to a lower percentage of system renewable energy for Washington customers in the near-term as compared to the Company’s current CEIP. Given these updates, the Company estimates by 2025 that 33 percent of Washington retail sales
will be served by renewable and non-emitting energy, and as discussed above, the Company will
substantially decarbonize its system and achieve CETA’s 2045 requirements almost a decade early.
Target Development
Updated interim target development is consistent with PacifiCorp’s Refiled 2021 CEIP, Chapter 1, where the Company’s Washington allocation of the updated CEIP-compliant portfolio of resources was analyzed based on an updated forecast of retail electric sales to Washington.13
This section discusses the assumptions that informed these updated interim targets. To estimate the amount and mix of energy forecasted to serve Washington customers for the 2023-2045 period, PacifiCorp summed annual generation from its qualifying resources allocated to Washington customers under the Washington Inter-Jurisdictional Allocation Methodology
(WIJAM) for existing resources and generally assumed that these assumptions hold into the future, in the absence of an agreed upon future allocation methodology.14 The allocations assumed for Washington in this update are the Company’s best estimate of future allocations at this time, and are best aligned with other ongoing filings in Washington.
To calculate the energy and the total amount of renewable and carbon non-emitting energy allocated to Washington customers, the company made the assumptions set forth below. Generally, where a resource is assumed to generate RECs, where one REC is generated for one megawatt-hour of renewable energy, the resource was assumed to generate CETA-compliant energy. In addition to REC-generating resources, it was assumed that all Washington-allocated energy from

13 PacifiCorp’s Revised 2021 CEIP can be found at:
https://apiproxy.utc.wa.gov/cases/GetDocument?docID=277&year=2021&docketNumber=210829. 14 The WIJAM and the 2020 PacifiCorp Inter-Jurisdictional Allocation Protocol (2020 Protocol) define how resources
and costs are allocated to Washington customers through December 21, 2023. The Washington Utilities and Transportation Commission approved the WIJAM and 2020 Protocol in its Final Order 09/07/12 in docket UE-191024
et. al., effective January 1, 2021. The company is in the process of negotiating its Multi-State Process (MSP) cost allocation methodology with the commissions and stakeholders in the six states it serves. More information can be
found in Volume I, Chapter 3.
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

non-emitting resources was also CETA compliant, namely hydroelectric, nuclear and hydrogen
non-emitting peaking plants.15 In summary, the resource allocation assumptions are: 1. Allocation of energy for all system renewable resources, existing and proxy, are allocated according to system-generation (SG) factors, consistent with the WIJAM.
2. Allocation of energy for new non-emitting proxy resources are allocated on SG factors,
consistent with the WIJAM. 3. Allocation of energy for all Washington qualifying-facilities (QFs) are assumed to be situs to Washington. No energy is allocated from QFs not originating in Washington, consistent with Washington Utilities and Transportation Commission policy.
4. Washington customers are assumed to participate in a limited set of emitting resources as
defined under the West Control Area Inter-Jurisdictional Allocation Methodology (WCA): a. Washington customers receive costs and benefits from PacifiCorp’s interest in the Colstrip Unit 4 and Jim Bridger Unites 1-4 thermal resources, subject to
elimination of all costs and benefits from coal-fueled Colstrip 4 and Jim Bridger
Units 3 and 4 until by the end of 2025. It is assumed that in the event a coal-fueled resource converts to gas before 2026, that Washington customers can participate until the end 2029. b. Washington customers participate in two gas-fired units, Chehalis and Hermiston,
through the end-of-life.
Given the assumed allocations of resource energy and costs to Washington, CETA-compliant energy is determined given the following:
1. For REC-generating resources, generation of CETA-compliant energy is consistent with
the company’s REC entitlement start and end date. 2. Customer preference and voluntary renewable resources were not assumed to generate RECs for the system or the state of Washington and thus are not included in the allocation of renewable energy.
3. All renewable and non-emitting resources were assumed to be CETA compliant,
including wind, solar, geothermal, hydro, nuclear and hydrogen non-emitting peaking plants. For renewable resources co-located with battery storage, RECs were assumed to be generated pre-storage; no RECs are generated at battery discharge. 4. Emitting generation (coal or gas-fueled resources) are not CETA compliant.

Washington retail electric sales were defined as total energy served to customers annually, net of distributed generation, existing and optimized energy efficiency and demand-side management (DSM) resources. Retail electric load does not include MWh delivered from Washington qualifying facilities under the federal Public Utilities Regulatory Policies Act of 1978 (PURPA).16
CETA compliance targets were calculated annually as a percentage of Washington retail electric

15 WAC 480-100-610(3) states that by January 1, 2045, each utility must ensure that “non-emitting electric generation
and electricity from renewable resources supply one hundred percent of all retail sales of electricity to Washington electric customers”.
16 RCW 19.405.020(36)(a)
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sales. Annual targets for CETA’s 2030 and 2045 requirements were calculated as a percentage of
Washington retail electric sales to be the total renewable and carbon non-emitting energy the Company estimates will be provided to Washington customers. For purposes of this CEIP, PacifiCorp relies on the use of unbundled RECs to satisfy the alternative
compliance component of the 2030 and 2031 greenhouse gas neutral standard. PacifiCorp may
meet up to 20 percent of its aggregate retail electric sales over the four-year compliance period with alternative compliance from January 1, 2030, through December 31, 2044. For further discussion specific to development of the CETA-compliant portfolio and interim
targets, please see subsection Interim Target Shortfall Resolution.
Specific Targets
Renewable energy targets, energy efficiency and demand response targets will evolve from the ongoing CEIP, based on updated outputs and analysis from this IRP Progress Report. The Company’s November 1, 2023 Biennial CEIP Update will provide updates to all general CEIP requirements, including specific targets.

Customer Benefit Indicators
As part of its CEIP compliance report to be filed July 1, 2023, PacifiCorp will report and track customer benefit indicators (CBIs) that are identified in Chapter 2 of the Company’s CEIP. These metrics will report on the progress made in each CBI as PacifiCorp moves through the four-year
CEIP cycle. Furthermore, PacifiCorp is considering additional input on the Company’s CBIs in
response to public comment and stakeholder feedback received in Docket UE-210829. Of note, the Washington Department of Health (DOH) recently updated the agency’s highly-impacted communities (HIC) analysis in January 2022.17 Based on this DOH update, the Company concluded there is one additional HIC located within PacifiCorp’s Washington service territory
compared to what was considered in the Company’s 2021 CEIP. The Company is in the process
of including this additional HIC within the baseline and will account for it when developing metrics for the July 1, 2023, compliance report. The process of updating the metrics for the July 1, 2023, filing will be based largely on survey
results. As was the case with the Company’s December 30, 2021, filing, the CBI metrics will
require PacifiCorp to use survey responses to identify energy burden for vulnerable populations in the Washington service area. This survey is expected to launch in April 2023 and will include both an email and telephone effort to accumulate necessary data.

17 See generally, Washington Department of Health, Information by Location (IBL) (available here:
https://doh.wa.gov/data-and-statistical-reports/washington-tracking-network-wtn/information-location).
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Specific Actions

This section provides updates on the Company’s supply- and demand-side resource actions taken over the past two-year period. As discussed below, the Company has procured substantial non-emitting and renewable resources and taken significant steps to improve or expand its demand-side resource programs and opportunities.
Supply-Side Resource Actions
The 2020AS RFP has concluded with the procurement of 1,792 MW of wind resources, 495 MW of solar additions, and 200 MW of battery storage capacity paired with solar. All of these resources
have 2024 or 2025 CODs and will contribute to PacifiCorp’s renewable energy and carbon reduction goals. PacifiCorp procures for its system needs across its six-state territory. Prior to the passage of CETA and with the 2020 procurement effort, there were no cost-competitive Washington bids and
therefore limited alignment with the CBIs that resulted from a 2021 stakeholder engagement process. Following the 2021 IRP filing, PacifiCorp issued its first request for proposal to take into
consideration the requirements of CETA. The ongoing 2022 all source request for proposals
(2022AS RFP) was filed in Washington and received approval in three states after a lengthy stakeholder process. It was subsequently issued to the market on April 29, 2022. PacifiCorp hired an independent evaluator (IE) to oversee the process, with the oversight of the Washington Commission. In December 2022, PacifiCorp bid twelve eligible self-build (benchmark) resources
into the 2022AS RFP, and on March 14, 2023, PacifiCorp received 302 bids from 74 developers
and 93 different projects sites across six states. A final shortlist is expected to be released by late Q2 2023 or early Q3 2023, with resources contracted by the end of Q4 2023. PacifiCorp will consider its Washington CBIs before making a final shortlist decision.
Demand-Side Resource Actions
Since the original CEIP filing, PacifiCorp has made the following changes and updates to demand-side resource programs to help increase benefits to named communities and achieve goals
informed by our Equity Advisory Group (EAG):18
Residential Energy Efficiency
• Enhanced incentives for windows in multi-family units on residential rate schedules. Initial
focus on buildings in highly impacted communities.
• Continued direct install residential lighting in multi-family units with focus in highly impacted communities.

18 These changes and updates were identified as CEIP Utility Actions in the 2022-2023 DSM Business Plan filed with
the 2022-2023 Biennial Conservation Plan on November 1, 2021 (Docket UE-210830). The same actions were included in the CEIP, and the 2023 Annual Conservation Plan filed November 15, 2022 (Docket UE-210830), included
an update on the Utility Actions.
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• Maintained and expanded general purpose lamp buy down in “dollar stores” in highly impacted communities.
• Continued manufactured home direct install duct sealing and lighting. Continue focus in highly impacted communities.
• Continued promoting new construction offerings for multifamily, and single family units. Continue focus in highly impacted communities.
• Develop pathways for non-electric, non-natural gas upgrades in named communities.
o Serve named community residential customers who use non-electric and non-
natural gas fuel sources in their primary heating systems by offering incentives for decommissioning these systems and installing ductless heat pumps.
Low Income Weatherization
• Increased funds available for repairs from 15 percent to 30 percent.
• Permitted installation of electric heat to replace permanently installed electric heat, space heaters or any fuel source except natural gas with adequate combustion air as determined by the Agency. The changes are designed to promote the installation of electric heat and
minimize use of wood heat, solid fuels or natural draft equipment in specific applications
where combustion safety (and indoor air quality) cannot be maintained.
Non-residential energy efficiency
• Increased outreach and participation for small businesses and named community small
businesses identified by census tract and rate schedule.
o Created a new offer within the current small business enhanced incentive offer targeting the smallest businesses using less than 30,000 kilowatt-hours per year and Named Community small businesses on Schedule 24.
o Targeted a portion of company initiated proactive outreach to small businesses
located in highly impacted communities. Continued to tie proactive outreach to approved small business vendor capacity to respond to customer inquiries.
• Offered approved small business lighting vendors a higher vendor incentive for completed lighting retrofit projects with small businesses located in highly impacted communities.
• For 2023, the program seeks to create a new offer within the current small business offer to include enhanced incentives for select non-lighting measures.
• Continue development of program materials in Spanish and increase outreach to Latinx and Tribal community groups.
Specific to energy efficiency actions, the company will document its progress regarding the CBIs and energy savings targets in its annual clean energy progress report filed on July 1st each year Specific to energy efficiency targets, PacifiCorp filed its 2023 Annual Conservation Plan on
November 15, 2022 (Docket UE-210830). This plan includes an updated forecast for 2022-2023 which indicates a shortfall relative to the two-year target established via the process for target setting established by the Energy Independence Act (WAC 480-109-100). The final results for 2022-2023 will be in PacifiCorp’s Biennial Conservation Report due June 1, 2024. On November 1, 2023, PacifiCorp will file its Biennial Conservation Plan with the targets for 2024-2025. Those
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targets will be based on updated information relative to the CEIP and will align with those accepted
from this ongoing two-year Energy Independence Act target setting process. PacifiCorp also has also taken actions to develop demand response resources to work towards stated interim targets. Since the original CEIP, PacifiCorp received approval for Schedule 106,
which is an enabling demand response tariff that supports multiple market driven programs.
Schedule 106 provides a regulatory framework that includes a fast and flexible change process while at the same time enabling transparent customer information for the benefit of all stakeholders. Each new demand response program will use Schedule 106 for enablement, communication, and tracking. The Company has taken the following program-specific demand
response actions in Washington:

Commercial and Industrial Curtailment A commercial and industrial program was approved and effective in December 2022. The program focuses on enrolling connected end use loads available during various dispatch periods. Event
communication and control occurs through a Program Administrator-provided, two-way
communications device (communicating via cellular signals) installed at the customer site.
Irrigation Load Control This program was approved and became effective in August 2022. It focuses on enrolling
agricultural irrigation pumps with the highest connected loads during the available dispatch hours
in the summer during the irrigation season with incentives differentiated based on dispatch notification option. The program relies on field-installed direct load control (DLC) devices to send signals to pumping equipment for reduction of irrigation loads for participating customers.

Bring your own Thermostat and Water Heater Direct Load Control
The company is preparing to file, for approval, a program to deliver curtailable end-use loads from residential HVAC equipment communicating through customers’ web-enabled thermostats and electric water heaters via Wi-Fi enabled communication devices. The Company is currently estimating an effective date in 2023 for this program.

Batteries This program is under consideration and is currently in the preliminary stages of planning. The program would potentially target residential – and possibly commercial – customers who have Wi-Fi connection to incentivize the use of individual batteries for system wide-integration in support
of overall grid management.
While the Company has made progress on these demand response actions since filing the CEIP, as described above, program implementation is just beginning to ramp up. As noted in the CEIP, “Total demand response volume is subject to change based on timing of programs and contract
negotiations.”19 As implementation and development of these new programs continues, progress
toward and change to the interim targets will likely occur as expectations regarding demand response volumes are informed by actual effective program dates, leading to improved planning

19 See CEIP page 22.
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estimates. Volumes attained by the end of the CEIP period, 2025, will likely be different from the
initial CEIP forecast of 37.4 MW. Specific to demand response actions, the company will document its progress regarding the CBIs and capacity savings targets in its annual clean energy progress report filed on July 1st each year.

Time-of-Use Pilots Beginning in May 2021, PacifiCorp launched residential and non-residential service time of use pilots. The residential pilot (Schedule 19) targets single family residential customers and is available for up to 500 customers on a first-come, first-served basis. The non-residential time of
use pilot (Schedule 29) targets non-residential customers with loads under 1,000 kW and is
available for up to 100 customers on a first-come, first-served basis.
Incremental Cost An update to the incremental cost calculation is provided for the remaining years in the CEIP period, 2023 – 2025. The CEIP portfolio, W-10 CETA, was specifically optimized and designed
to meet CETA standards. This portfolio is contrasted to the alternative lowest reasonable cost portfolio as defined in rule and is denoted P-SC or referred to as the Alternative Portfolio.20 Any differences in cost between the CEIP portfolio and the Alternative Portfolio are considered incremental costs, costs directly resulting from actions taken to comply with requirements under RCW 19.405.040 or 19.405.050. These incremental costs include items like CETA-driven
impacts to electricity generation, energy efficiency, new programs to support customers, and program management, that can be measured for the current CEIP period. The methodology to calculate the updated incremental cost is consistent with the methods described in the refiled 2021 CEIP. Only the modeled IRP-based costs were updated at this time.
Given the updated portfolio outcomes, the incremental costs to comply with CETA is $2.13 million on average per year.
Interim Target Shortfall Resolution
To develop the CEIP portfolio, the base portfolio, P-SC, was evaluated against CETA requirements that Washington-supplied energy would be 100% greenhouse gas neutral with up to 20 percent of this amount supplied by unbundled RECs beginning in 2030, and 100 percent clean
and non-emitting by 2045.
Given the system optimized portfolio under the SCGHG price policy assumption and assumed resource allocations to Washington customers, the Company identified a small compliance shortfall in 2030 and 2031. In years 2032 and beyond, the portfolio resources generated enough
renewable and non-emitting energy to Washington to meet 100 percent of need. These
compliance shortfalls were identified by calculating the amount of additional renewable or non-emitting energy that would be needed to meet at least 80 percent of Washington retail sales.
20 Several portfolios were developed specific to Washington CETA legislation and are defined in Volume I,
Chapter 8.
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A compliance shortfall of 67 MW of average annual capacity was identified in 2030, and a
slightly larger shortfall of 72 MW average annual capacity resulted for 2031. To reach the target of at least 80 percent non-emitting energy in 2030-2031 at least-cost, and without the need for additional transmission lines, small-scale renewable capacity was added in
Yakima, Washington. Specifically, 120 MW of installed capacity of small-scale solar and 120
MW of installed capacity of small-scale wind was added in Washington in 2030. The incremental small-scale resources were added only for CETA-compliance, on top of an optimized system portfolio developed under the SCGHG price policy assumption, as shown in Figure O.2. Thus, the incremental small-scale solar and wind was allocated situs to Washington
and would represent an incremental cost in 2030 and 2031.

Figure O.2 - Incremental Portfolio Change: W-10 CETA delta P-SC
These incremental actions resulted in the CEIP-compliant portfolio, W-10 CETA, and the associated interim targets and incremental costs.
Revenue Requirement Methodology
Incremental costs included for consideration in this CEIP can be broadly considered in two categories – IRP modeled incremental costs, and non-IRP modeled incremental costs. IRP
modelled incremental costs were identified through the comparison of changes in investment
costs between the CEIP portfolio and the Alternative Portfolio, described above, for the years 2023 - 2025. Per rule WAC 480-100-660(1), the only differences in investment decisions between the two portfolios described are a direct result of CETA requirements, determined to be met in a least-cost least-risk manner. Incremental investments and expenses were identified from
the comparison of the two portfolios and summarized on an annual, nominal and levelized basis
for the remaining compliance years in the CEIP. Table O.2 summarizes the resource-driven
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incremental expenses identified. However, note that the column for 2022 was not updated and is
equivalent to the modeled incremental cost shown in the Company’s current CEIP.

Table O.2 - Annual Modeled Impacts of CETA
There are no incremental resource additions in the CETA-compliant portfolio during the CEIP compliance window. Any differences in the annual modeled costs over the period are due to negligible movements in dispatch.
It is assumed that other non-modeled costs, as presented previously in the revised 2021 CEIP, have not changed and are shown in Table O.3.

Table O.3 - Non-modeled Impacts of CETA ($million)

CETA Expenses 2023 2024 2025 Description of Cost Item
CEIP Management, Coordination & Communication 0.57 0.58 0.60
Additional Staffing to help
coordinate, facilitate and strategic planning for CEIP
Enhanced Outreach & Communication 0.39 0.39 0.40 Outreach and materials for EAG and Public meetings
External Data Support 0.17 0.18 0.18 Vendor expense for data support
CETA-specific DSM Program Expenses 1.26 1.29 1.32
Costs incurred to enhance reach and equitable distribution of DSM programs
Total 2.40 2.45 2.50 Taking the estimated incremental costs identified based on methodologies described in this report, the company calculated an annual revenue requirement using the standard revenue requirement formula:

Revenue Requirement = Rate of Return x (Net Rate Base) + Operating Costs

($million)2022 2023 2024 2025
Fuel Costs - (0) 0 (1)
Other Variable - 0 0 0
Energy Efficiency - - 0 -
Net Market Purchases - (0) (0) (3)
Emissions - 1 0 2
Deficiency - - (0) (0)
Fixed Costs - - (0) 0
Total - 0 (0) (2)
Compliance Year
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Using the above formula, the estimated annual revenue requirement for the remaining years in the
compliance period is as follow, presented in Table O.4.
Table O.4 - Revenue Requirement of Cost Estimates
Compliance Year
$-Millions 2022 2023 2024 2025
Revenue Requirement
Fixed Costs1 - - (0.00) 0.00

Variable Costs
Fuel Costs - (0.03) 0.03 (0.68)
Variable O&M - 0.00 0.01 0.04
Energy Efficiency - - 0.00 -
Net Market Purchase - (0.04) (0.12) (3.11)
Emissions - 0.54 0.10 2.16
Deficiency - - (0.07) (0.06)
Total Variable Costs - 0.47 (0.04) (1.64)

Administrative & General
DSM Program Costs 1.24 1.26 1.29 1.32
Outreach Costs 0.40 0.37 0.38 0.39
Materials 0.01 0.01 0.01 0.01
Staffing 0.56 0.57 0.59 0.60
Data Support 0.17 0.17 0.18 0.18

Total Revenue Requirement 2 2.38 2.86 2.40 0.86
Average Revenue Requirement 2.13

Notes:
1. Incremental fixed cost are identical between the CEIP portfolio (W-10 CETA) and Alternative Portfolio (P-SC) during the CEIP compliance window. Fixed costs are reported in the respective portfolios at a nominal and levelized basis, which reflects both a return on and return of component.
2. Estimated revenue requirement is calculated based on incremental costs derived by comparing IRP portfolios. Actual cost recovery will ultimately be determined by the prevailing cost allocation methodology approved in Washington at the time recovery is sought.
The annual threshold for Alternative Means of Compliance as stated and calculated in the Revised
CEIP filed March 13, 2023, has not changed and is equal to $16,667 million. Thus, based on current forecasts, the estimated incremental costs identified for implementation of CETA from 2022 to

PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

2025 are within the annual threshold amount. As such, the Company will not rely on RCW 19.405.060(3) as a means of alternate compliance to achieve CETA’s requirements. Public Participation

The Company has engaged in various activities to increase public participation in the Company’s IRP and CEIP processes. These specific actions, outreach methods and timing, and addressing barriers to participation and internal stakeholder development are discussed below.
Specific Actions
The Company has taken the following actions to promote equity and engagement within its Washington service area. These include:

Formed Equity Advisory Group (EAG): The EAG was assembled in 2021 to help inform and advise the Company on the issues most important to the communities that PacifiCorp serves in Washington. The EAG comprises nine representatives from highly impacted communities and vulnerable populations within the Company’s Washington
service area, including Yakima, Yakama Nation, and Walla Walla. These members have
expertise on equity-related topics, such as the health of vulnerable populations and programs for low-income customers. The EAG meets regularly and provides significant input on the Company’s CBIs, metrics included in the CEIP, and how the Company plans and operates within its Washington service area.

Development of CBIs: Consistent with CETA, the Company is committed to ensuring that the benefits from the transition to clean energy are broadly shared and equitably distributed among all customers, with a specific focus on named communities. PacifiCorp
has partnered with stakeholders and advisory groups, including the EAG, to identify the
highest priority benefits to customers and identify potential barriers and burdens that may prevent some customers from receiving those benefits. These efforts have resulted in nine CBIs and associated weighting factors to evaluate the equitable distribution of benefits. This allows the Company to assess and monitor the impacts of each proposed program,
action, and investment. In addition, the CBIs were included in the Company’s most
recent CEIP to inform utility action, focusing on the named communities that were identified within the Company’s Washington service area.

Established Utility Actions within the CEIP: PacifiCorp committed to and made
several changes to residential and non-residential customer energy efficiency programs to
increase the focus on delivery of benefits to named communities. These utility actions were informed on input received from the EAG and CBIs. The same utility actions will be included in the 2022-2023 Biennial Conservation Plan, and updates for 2023 will be included in the 2023 Annual Conservation Plan. These utility actions include modifications to the low-income weatherization program that the Company filed on
December 21, 2021. These changes included, but were not limited to, expanding tariff applicability for the installation of energy efficiency improvements. Funds available for
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

repairs were also increased from 15 percent to 30 percent of the annual reimbursement on
energy efficient measures and income guidelines were updated to be consistent with RCW 19.405.020(25). Before these changes, some income-qualified homes could not receive energy efficiency improvements due to the extent of critical maintenance needed before the energy efficiency improvements could be made.

Establish an Electric Vehicle (EV) grant program: PacifiCorp established EV programs detailed in PacifiCorp’s Washington Transportation Electrification Plan. On May 20, 2022, PacifiCorp filed its 2022 “Washington State Transportation Electrification Plan” with the Washington Utilities and Transportation Commission under Docket UE-
22035921. PacifiCorp supplemented its original filing with an addendum filed on
September 28, 2022. This is PacifiCorp’s first filed TEP since enabling legislation was enacted in 2019. The Commission acknowledged the plan on October 27, 2022, enabling PacifiCorp to begin development of the proposed programs in the TEP inclusive of a communities grant program, outreach and education program, and managed charging
pilot program. These programs would broaden the previous EV programs by allowing for
multiple project types to participate with benefits and preference targeted towards named communities. The overall goal is to provide exploratory programs that will help to plan, promote, or deploy electric transportation technology and projects within Named Communities. Looking ahead, PacifiCorp is working with its Equity Advisory Group and
the Washington Utility and Transportation Commission and other stakeholders to review
draft program and pilot application prior to filing in Q2 of 2023. PacifiCorp anticipates launch of program and pilots in Q3 of 2023.

Modified the Low-Income Bill Assistance Program: PacifiCorp’s low-income bill
assistance (LIBA) program was established in 2003. LIBA provides a tiered discount
based on income levels. Previously, LIBA was designed to provide credits to income-eligible households on monthly usage over 600 kWh and included an annual enrollment cap. Consistent with the requirements in RCW 19.505.120 and consultation with the Low-Income Advisory Group, the Company proposed modifications to its program. In
particular, the Company proposed to (1) increase the maximum income threshold for the
program consistent with RCW 19.405.020(25), (2) modify the discount from a per kWh above 600 kWh, to a percentage discount of the net bill, with the discount level based on household size and income; and (3) eliminate the annual enrollment cap. These changes were allowed to go into effect on August 1, 2021.

PacifiCorp also hired Empower Dataworks to prepare a 2022 Energy Burden Assessment (EBA) for the Company’s residential customers in Washington. In the EBA, Empower Dataworks highlighted that the LIBA program design is very good at targeting benefits to higher burden customers and program administration. It also noted that the overhead
costs are very efficient relative to other programs in the state, and praised the great
coordination between PacifiCorp and the local community action agencies on providing culturally appropriate marketing and program designs. PacifiCorp partners with three

21 Materials available online at UTC Case Docket Document Sets | UTC (wa.gov)
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agencies to administer and deliver the program: Blue Mountain Action Council (BMAC)
serves Columbia, Garfield, and Walla Walla counties, Opportunities Industrialization Center of Washington (OIC) serves Upper Yakima County, and Yakima Valley Farm Workers Clinic dba Northwest Community Action Center (NCAC) serves Lower Yakima County.
Continued and Expanded Outreach
To ensure consistent outreach, PacifiCorp continues to use all of the engagement methods included
in its CEIP, including PacifiCorp’s CEIP and IRP dedicated website; email updates; fact sheet and flyers; bill inserts and bill messages; interactive voice response; social media, paid and press media; text message notices; partner channels; community surveys; CEIP Public Meetings and Technical Conferences; EAG Meetings; existing advisory groups and EAG pre-meeting materials; and meeting summaries.
These engagement methods attempt to further facilitate durable community relationships. Examples of specific continued outreach include: - PacifiCorp’s Washington EAG began meeting in 2021 and has continued to hold meetings
to, in part, support CEIP development and implementation. These meetings have continued into 2023, and have offer in-person and virtual meeting opportunities throughout the year; - PacifiCorp’s initial public participation outreach included both telephone and email and was designed to inform existing advisory groups (including the IRP Public Input Process) of the opportunity to provide feedback, as well as to form the Washington EAG;
- PacifiCorp continues to utilize its Washington Clean Energy Transformation Act & Equitable Distribution of Benefits webpage and the Integrated Resource Plan webpage to provide information to the public regarding how to participate in meetings, the development of the CEIP and the development of the IRP; - PacifiCorp’s outreach for both the DSM Advisory Group and the Low-Income Advisory
Group continues to occur by email to participants on the distribution list; and - The company has set up a dedicated email address, [e-mail], that is posted on the webpage to facilitate timely responses to any stakeholder questions. Additionally, PacifiCorp encouraged members of the public who wanted to participate in the development of the CEIP to join the company’s email list, which was used to communicate
upcoming meetings, meeting materials, and other opportunities for education and feedback. In addition to continued outreach, the Company has expanded its Public Participation outreach methods to draw in more diverse customer interests. For example:
- PacifiCorp developed a survey that targets our broader Washington customer base to gather input on the development of the CEIP. The survey was made available in English and Spanish between July 2, 2021, and August 10, 2021. There were separate versions for residential and non-residential customers. Survey results were prepared, summarized, and
posted on the Washington Clean Energy Transformation Act & Equitable Distribution of
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Benefits webpage. Customer feedback was incorporated into the Customer Benefit
Indicator (CBI) weighting process. PacifiCorp continues to explore methods to improve these surveys, and plans to use similar outreach methods in 2023. - PacifiCorp held 3 technical conferences on the CEIP development process that were targeted for parties interested in a deeper examination of the CEIP. PacifiCorp is open to
additional CEIP technical conferences.
The Company welcomes continues to explore—and welcomes helpful suggestions—for expanded public participation methods for future CEIP planning cycles.
Addressing Barriers to Participation
The Company continues to address barriers to participation, and support inclusion and accessibility in the Company’s CEIP and IRP planning processes. For example PacifiCorp:
- Now offers hybrid meeting formats for its EAG meetings, where members can attend meetings online or in-person. Initially, the COVID-19 pandemic prevented in-person gatherings from taking place, making virtual meetings necessary. Over time, the need for virtual meeting formats lessened, giving the group space to explore other ways to connect,
and various stakeholders expressed an interest for in-person meeting options as well. PacifiCorp held its first hybrid meeting for the Washington EAG in March 2023. The majority of the participants attended in person. The company intends to continue to offer a mix of online and in-person meeting options in the future. - Continues to offer Spanish translation of meeting materials, and have interpreters present
at public participation meetings. - Continues to seek input from the EAG and public to foster inclusion, equity, and continuing to learn about the ways that the company can better communicate to meet the cultural needs of its communities. - Continuing to ensure that information is available in broadly understood terms for all in
the community, and ensuring that customers have access to information through various accessible formats. - Has continued engagement with its on-going EAG, and stakeholders interested in the CEIP development process.
These actions to address barriers to participation help PacifiCorp identify specific actions that support initiatives to improve health, safety, and well-being of its communities, and PacifiCorp continues its CEIP public participation process to ensure open, transparent, and accessible processes.
Internal Stakeholder Development
PacifiCorp is also making efforts to promote equity through internal stakeholder development.
To achieve results in this arena, PacifiCorp is developing and equipping internal stakeholders
with adaptive leadership skills, education to build intercultural competency, and access to a devoted core team supporting an equity lens on stakeholder engagement. This has included:
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

• Outside subject matter expertise and facilitation. The Company has engaged E Source as its stakeholder facilitator and content support developer, who acts as an accountability partner for internal stakeholder development. This accountability allows a value chain
that creates and strengthens our internal equity decision-making lens and ensures that it
bears fruit in our deliverables and stakeholder engagement, and this consequently will help achieve equitable results in the communities the Company serves.
• Building adaptive leadership skills. The Company held an adaptive leadership in equity
workshop for key PacifiCorp employees who work on external engagement and customer
and community solutions. This workshop was held in December 2022 and focused on acknowledging and finding agreement on the value of building a safe and supportive space to grow individual’s adaptive leadership skills and provide tools, resources, and guidance in our shared journey. This workshop is important because developing an equity
decision-making lens requires understanding and acceptance on the individual and
corporate level of intercultural competency. Further, it requires a commitment to self-awareness, learning, application (success and lessons learned), and growth.
• Building intercultural communication skills. The Company plans to host an internal
workshop in the spring of 2023, that will equip its employees with the tools necessary for effective intercultural communication. While it is expected that most subscribe to the Golden Rule – do unto others as you would like done unto you – in communications, this stops short of intercultural competency. The golden rule is based on a monocultural worldview and assumes all groups value the same thing. This workshop aims to support
trust building and the adaption of individual perspective and behaviors to connect better, communicate and engage others.
• Benchmarking and building intercultural competency. The Company will administer
the Intercultural Development Inventory (IDI) Survey, considered an international benchmark, in the fall of 2023. Core team members will be debriefed privately on their scores and given individual development and coaching plans
PACIFICORP – 2023 IRP APPENDIX O – WASHINGTON CLEAN ENERGY ACTION PLAN

402
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS

APPENDIX P – ACRONYMS
AB = Assembly Bill
AC = alternating current
ACE = Affordable Clean Energy Rule
ACE = Area Control Error
AEG = applied energy group
AFSL = average feet (above) sea level
AFUDC = allowance for funds used during construction
AGC = Automatic Generation Control
AH = Ampere hour
A/m = Amperes per Meter
AMI = Advance Metering Infrastructure
AMR = Automated Meter Reading
ARO = asset retirement obligation
ATC = Available Transmission Capacity (Available Transfer Capacity?)
AVR = Automatic Voltage Regulator
AWEA = American Wind Energy Association
BA – Balancing Authority
BAA = Balancing Authority Area
BART = Best Available Retrofit Technology
BCF/D = billion cubic feet per day
BES = Bulk Electric System
BLM = Bureau of Land Management
BMcD = Burns and McDonnell
BPA = Bonneville Power Administration
BSER = best system of emission reduction
Btu = British thermal unit
CAES = compressed air energy storage
CAGR = compounded annual average growth rate
CAIDI = Customer Average Interruption Duration Index
CAISO = California Independent System Operator
CAP = Community Action Program
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS
CARB = California Air Resources Board
CARI = Control Area Reliability Issues
CCCT = Combined Cycle Combustion Turbine
CCGT = Combined Cycle Gas Turbine
CCR = coal combustion residual
CCS = carbon capture and sequestration / Utah Committee of Consumer Services
CEC = California Energy Commission
CETA = Clean Energy Transformation Act
CF = capacity factor
CFL = Compact Fluorescent Light Bulb
CIPS = Critical Infrastructure Protection Standards
CIS = Corporate Information Security
CO = carbon monoxide
CO2 = carbon dioxide
Cogen = Cogeneration
COMPASS = Coordinated Outage Management Planning and Scheduling System?
CPA = Conservation Potential Assessment
CPU = Clark Public Utilities / cost per unit
CPUC = California Public Utilities Commission
CREA = Columbia Rural Electric Association
CSP = concentrated solar power
CTG = Combustion Turbine Generator
CUB = (Oregon) Citizen’s Utility Board
DC = direct current
DF = duct firing
DG = Distributed Generation
DOE = Department of Energy
DPU = Utah Division of Public Utilities / Distribution Protection Unit (relay)
DR = Demand Response
DRA = Division of Ratepayer Advocates
DSM = demand-side management
EBIT = Earnings before Interest and Taxes
EDAM = extended day-ahead market
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS

EE = Energy Efficiency
EEI = Edison Electric Institute
EIA = Energy Information Administration
EIM = Energy Imbalance Market
ELCC = Effective Load Carrying Capacity
EPA = Environmental Protection Agency
EPC = engineering, procurement, and construction
EPM = Energy Portfolio Management System
ERC = emission rate credit
ETO = Energy Trust of Oregon
EUBA = Electric Utility Benchmarking Association
EUI = Energy Utilization Index
EUL = effective useful life
EV = Electric Vehicle
FCC = Federal Communications Commission
FCRPS = Federal Columbia River Power System
FERC = Federal Energy Regulatory Commission
FIP = federal implementation plan
FIT = Feed-In Tariff
FLPMA = Federal Land Policy Management Ace
FOTs = Front Office Transactions
FRAC = Flexible Resource Adequacy Capacity
GAAP = Generally Accepted Accounting Principles
GBP = Great Britain Pound
GE = General Electric
GFCI = Ground Fault Circuit Interrupter
GHG = Greenhouse Gas
GIC = Generation Interconnection Contract
GIS = Geographic Information System
GPS = Global Positioning System
GRC = General Rate Case
GRID = Generation and Regulation Decision Model (used for net power cost pricing calc and
QF avoided cost calc)
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS
GT = Gas Turbine
GW = Gigawatt
GWh = gigawatt-hours (gigawatt)
H = Hour
HB = House Bill
HCC = Hydro Control Center
HRSG = Heat Recovery Steam Generator
HVAC = heating, ventilation, and air conditioning
Hz = Hertz
IBEW = International Brotherhood of Electrical Workers
IC = internal combustion
ICE = Intercontinental Exchange
IECC = International Energy Conservation Code
IEEE = Institute of Electrical and Electronic Engineers
IGCC = integrated gasification combined cycle
IHS = Information Handling Services
ILR = Inverter Loading Ratio
IOU = Investor Owned Utility
IPC = Idaho Power Company
IPP = Independent Power Producer
IPOC = Idaho Power Company
IPUC = Idaho Public Utility Commission
IRA = Inflation Reduction Act
IRP = Integrated Resource Plan
IS = Information Systems
ISO = international organization for standardization / Independent System Operator
IT = Information Technology
ITC = Investment Tax Credit
K = kilo (thousand)
Kv = kiloVolt
kW = kilowatt
kWh = kilowatt-hour
kW-yr = Kilowatt-Year
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS

kV = kilovolt
kVa = kilovolt-ampere
kVAr = kilovolt-ampere-reactive
kVArh = kilovolt-ampere-reactive-hour
Lb = Pound
LCOE = Levelized Cost of Energy
LED = light emitting diode
Li-Ion = lithium-ion battery
Lm = lumens
LNG = Liquefied Natural Gas
LOLH = loss of load hour
LRA = Local Regulatory Authority
LSE = load serving entities
MATS = Mercury and Air Toxics Standards
MEHC = MidAmerican Energy Holdings Company
MMBpd = Million barrels of oil per day
MMBtu = Million British thermal units
MSP = Balancing Authority Area / Multi-State Process
MVA = megavolt-ampere
MVAr = megavolt-ampere-reactive
MVA LTC = megavolt-ampere, load tap changing
MW = Megawatt
MWh = megawatt hour
$MWh = dollars per megawatt hour
NAAQS = National Ambient Air Quality Standards
NAPEE = National Action Plan for Energy-Efficiency
NCM = nickel cobalt manganese (sub-chemistry of Li-Ion)
NEEA = Northwest Energy Efficiency Alliance
NEEP = Northeast Energy Efficiency Partnerships
NEMA = National Electrical Manufacturer’s Association
NEMS = National Energy Modeling System
NERC = North American Electric Reliability Corporation
NH3 = Ammonia
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS
NOAAF = National Oceanic and Atmospheric Administration Fisheries
NRC = Nuclear Regulatory Commission
NOx = Nitrogen Oxides
NPV = net present value
NQC = Net Qualifying Capacity
NSPS = new source performance standards
NTTG = Northern Tier Transmission Group
NWEC = NW Energy Coalition
NWPCC = Northwest Power and Conservation Council
O&M = operations and maintenance
OAR = Oregon Administrative Rules
OASIS = Open Access Same Time Information System
OATT = Open Access Transmission Tariff
ODOE = Oregon Department of Energy
ODOT = Oregon Department of Transportation
OE = Owner’s Engineer
OEM = Original Equipment Manufacturer
OFPC = Official Forward Price
OMS = Outage Management System / Operations Mapping System
OPUC = Oregon Public Utility Commission
ORS = Oregon Revised Statutes
OTR = Ozone Transport Rule
PAC = PacifiCorp
PACE = PacifiCorp East?
PaR = Planning and Risk Model
PC = pulverized coal
PCB = Polychlorinated Biphenyls
PC CCS = pulverized coal equipped with carbon capture and sequestration
PDDRR = Partial displacement differential revenue requirement methodology (OR QF)
PG&E = Pacific Gas & Electric
PGE = Portland General Electric
PHES = pumped hydro energy storage
PJM = no definition
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS

PM = particulate matter
PM2.5 = Particulate Matter 2.5 microns and larger
PM10 = Particulate Matter 10 microns and larger
PNUCC = Pacific Northwest Utility Coordinating Council
POU = Publicly Owned Utility
PP = Pacific Power
PPA = Power Purchase Agreement
Ppb = parts per billion
PP&L = Pacific Power & Light Co.
ppmvd@15%02 = parts per million, dry-volumetric basis, corrected to 15% Oxygen (O2)
PRM = Planning Reserve Margin
PSC = Public Service Commission
PSE = Purchasing-Selling Entity
Psia = Pounds per Square Inch-Absolute
PTC = Production tax credit
PTO = Participating Transmission Owner
PTP = point to point
PUC = Public Utility Commission
PURPA = Public Utility Regulatory Policies Act
PV = photovoltaic
PVRR(d) = present value revenue requirement (delta)
PWC = PricewaterhouseCoopers
QC = Qualifying Capacity
RA = Resource Adequacy
RCRA = Resource Conservation and Recovery Act
RCW = Revised Code of Washington
REA = Rural Electrical Administration / Rural Electrification Administration
REC = renewable energy credit (certificate) / Rural Electric Cooperative
RFI = request for information
RFM = Rate Forecasting Model
RFP = Request for Proposal
RH = Relative humidity
RICE = Reciprocating Internal Combustion Engine
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS
RMP = Rocky Mountain Power / Resource Management Plan
RPS = Renewable Portfolio Standard
RTO = Regional Transmission Organization
RTF = Regional Technical Forum
RTP = real-time pricing
RVOS = Resource Value of Solar
SAIDI = System Average Interruption Duration Index
SAIFI = System Average Interruption Frequency Index
SB = Senate Bill
SCCT = Simple Combined Cycle Turbine
SCPC = Super-critical pulverized coal
SCPPA = Southern California Public Power Authority
SCR = selective catalytic reduction system
SEC = Securities and Exchange Commission
SEEM = Simple Energy Enthalpy Model
SEPA = Solar Electric Power Association
SIP = state implementation plan
SF = Senate File
SF6 = Sulfur Hexafluoride
SNCR = selective non-catalytic reduction
SO = System Optimizer
SO2 = Sulfur Dioxide
SOx = Sulfur Oxide / Sarbanes-Oxley Act
SRSG = Southwest reserve sharing group
SSR = supply side resource (table)
STEP = Sustainable Transportation and Energy Plan
STG = Steam turbine generator
SWEEP = Southwest Energy Efficiency Project
T&D = Transmission & Distribution
th = Therm
TPL = transmission planning assessment
UAE = Utah Association of Energy Consumers
UDOT = Utah Department of Transportation
PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS

UMPA = Utah Municipal Power Agency
UNIDO = United Nations Industrial Development Organization
UP&L = Utah Power & Light Co.
UPC = Use per Residential Customer
UCE = Utah Clean Energy
UCT = Utility Cost Test
VERs = Variable Energy Resources
V = volt
VA = Volt-ampere
VDC = Volts Direct Current
VOC = volatile organic compounds
W = Watts
WAC = Washington Administrative Code
WACC = weighted average cost of capital
WAPA = Western Area Power Administration
WCA = West Control Area
WECC = Western Electricity Coordinating Council
Wh = Watt-hour
WIEC = Wyoming Industrial Energy Council
WPSC = Wyoming Public Service Commission
WRA = Western Resource Advocates
WREGIS = Western Renewable Generation Information System
WSEC = Washington State Energy Code 2015
WSPP = Western Systems Power Pool
WTG = wind turbine generator
WUTC = Washington Utilities and Transmission Commission

PACIFICORP – 2023 IRP APPENDIX P – ACRONYMS