20241230CL_2025 Electric IRP.pdf

' 11
RECEIVED
2024 December 30
Avista Corp. IDAHO PUBLIC
1411 East Mission P.O. Box 3727 UTILITIES COMMISSION
Spokane, Washington 99220-0500
Telephone [phone]
Toll Free 800-727-9170 Chse 1 Vll.AVUL-24-13
December 30, 2024
Secretary
Idaho Public Utilities Commission
11331 W. Chinden Blvd. Bldg. 8, Ste. 201-A
Boise, Idaho 83714
RE: Case No. AVU-E-24-_-Avista's 2025 Electric Integrated Resource Plan
Dear Secretary:
Avista Corporation, dba Avista Utilities, submits for filing with the Commission its final 2025
Electric Integrated Resource Plan (IRP). Supporting documents can be found at
https://myavista.com/about-us/integrated-resource-]21anning.
Please note that certain sections of the Appendices, Appendix H and I, have CONFIDENTIAL
information.
If you have any questions regarding this filing,please contact James Gall at 509-495-2189 or John
Lyons at 509-495-8515.
Sincerely,
/J,/$" FageeQd
Shawn Bonfield
Sr. Manager of Regulatory Strategy & Policy
509-495-2782
Shawn.bonfieldgavistacorp.com

2025
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Safe Harbor Statement
This document contains forward-looking statements. Such statements are subject to a
variety of risks, uncertainties and other factors, most of which are beyond the Company's
control, and many of which could have a significant impact on the Company's operations,
results of operations and financial condition, and could cause actual results to differ
materially from those anticipated.
For a further discussion of these factors and other important factors, please refer to the
Company's reports filed with the Securities and Exchange Commission. The forward-
looking statements contained in this document speak only as of the date hereof. The
Company undertakes no obligation to update any forward-looking statement or
statements to reflect events or circumstances that occur after the date on which such
statement is made or to reflect the occurrence of unanticipated events. New risks,
uncertainties and other factors emerge from time to time, and it is not possible for
management to predict all of such factors, nor can it assess the impact of each such factor
on the Company's business or the extent to which any such factor, or combination of
factors, may cause actual results to differ materially from those contained in any forward-
looking statement.
Avista Corp 2025 Electric IRP 2

Production Credits
Primary Electric IRP Team
Name Title Contribution
James Gall Manager of Resource Analysis IRP Core Team
John Lyons Senior Policy Analyst IRP Core Team
Lori Hermanson Senior Power Supply Analyst IRP Core Team
Mike Hermanson Senior Power Supply Analyst IRP Core Team
Tom Pardee Natural Gas Planning Manager IRP Core Team
Michael Brutocao Natural Gas Analyst IRP Core Team
Grant Forsyth Chief Economist Load Forecast
Kim Boynton Mgr. of Energy Efficiency, Planning &Analysis Energy Efficiency
Leona Haley Energy Efficiency Program Manager Demand Response
Dean S ratt Senior System Planning Engineer Transmission Planning
Damon Fisher Principle Engineer Distribution Planning
Electric IRP Contributors
Name Title Contribution
Scott Kinney VP of Energy Resources Energy Supply
Kevin Holland Director of Energy Supply Energy Supply
Clint Kalich Energy Resource Planning Advisor Energy Supply
Chris Drake Manager of Resource Optimization Energy Supply
Ryan Finesilver Wholesale Marketing Manager Energy Supply
Annette Brandon Wholesale Marketing Manager Energy Supply
Tamara Bradley Customer Engagement Manager Community Outreach
Kelly Den el Energy Resource Project Manager CEIP
Darrell So ars Manager Corporate Environmental Compliance Environmental
Janna Loeppky Greenhouse Gas Compliance Program Mgr. Environmental
John Gross Manager of System Planning System Planning
Erik Lee Principal Engineer System Planning System Planning
Austin Oglesby Energy Efficiency Analyst Energy Efficiency
Megan Pinch Manager of Energy Efficiency Programs Energy Efficiency
Ana Matthews Senior Energy Efficiency Program Manager Energy Efficiency
Rendall Farley Manager of Electric Transportation Clean Energy Solutions
Kit Parker Renewables Products and Services Manager Clean Energy Solutions
Shawn Bonfield Senior Manager of Regulatory Policy Regulatory
Amanda Ghering Regulatory Affairs Analyst Regulatory
Jared Webley Senior Communications Manager Communications
Catherine Mair Communications Manager Communications
Contact contributors via email by placing their names in this email address format:
[e-mail]
Avista Corp 2025 Electric IRP 3

Executive Summary
2025 Electric IRP
Executive Summary
The Integrated Resource Plan (IRP) is a comprehensive planning document outlining
Avista's strategy to meet the future energy needs of its customers in a cost-effective and
sustainable manner. It involves analyzing different energy resources, such as wind, solar,
plant upgrades, energy storage, natural gas, and energy efficiency to find the best mix of
resources to ensure a reliable and affordable energy supply. The IRP process includes
public input, regulatory, and peer review to ensure the plan aligns with IRP requirements
and expectations. Essentially, the IRP serves as a roadmap for the utility's long-term
energy planning and decision-making as it begins its resource acquisition process.
Since 2014, Avista's annual energy demand has remained flat with an annual growth rate
of 0.09% per year. Between recent economic growth in the community and a new large
load beginning in August 2024, the 2026 loads are forecasted to be 4.5% higher than
2023 levels, an increase of 50 aMW. Absent any additional new large loads, annual
energy growth is projected to continue to be slow over the next seven years. Load levels
are relatively flat due to energy efficiency and a reduction of line losses from exiting
Colstrip at the end of 2025. Over the next 20 years, annual growth is expected to be
0.91% on average with the last 10 years of the plan growing at 1.4% annually with more
electrification of buildings and transportation.
While annual average energy growth is historically flat, both winter and summer peak
loads recently hit all-time highs. By 2024, summer peak load was 8.8% higher and winter
peak loads were 12.2% higher' than 2014 actual peak load. Avista anticipates peak
growth to continue to grow faster than energy. The summer peak load is forecast to grow
by 1.14% annually and winter peak by 1.12% over the next 20 years. The last 10 years
of the plan show significantly higher load growth with 1.7% annual peak load growth due
to expectations of building and transportation electrification. Figure 1 summarizes Avista's
historical and forecasted demand.
Peak loads are adjusted for demand curtailment.
Avista Corp 2025 Electric IRP 4

Executive Summary
Figure 1: Customer Load Forecast
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Energy efficiency continues to be a cost-effective method to reduce customer demand
and avoid new generating resources. Customer load today would be 156 aMW higher
absent these efforts. In 2045, energy efficiency is expected to reduce load by an additional
105 aMW, thus meeting 32% of future demand. The top energy efficiency methods to
reduce future load include offering incentives for more efficient lighting, space heating
and cooling, and water heating. The 2026-2027 biannual energy efficiency target in
Washington is 73,672 MWh and for Idaho is 19,595 MWh.
In 2026, Avista's generating capability is approximately 52% from clean energy sources
and 48% from natural gas resources as shown in Figure 2. Absent the economic dispatch
of natural gas generators, Avista could generate 1,569 aMW in normal weather
conditions. Given the 2026 load forecast is 1,165 aMW, Avista is long on energy
resources and intends to be long on generating capability to prepare for the risk of low
hydro conditions and to meet peak load creating energy length. The excess energy is
sold to reduce Avista's customer rates when beneficial for our customers.
Due to Avista's energy position length compared to demand; capacity planning for
sustained peak hours is Avista's most significant constraint on the system. Due to recent
peak load growth, the Company is in a short to even position over the next three years
during both summer and winter peaks. Avista uses a 24% planning reserve margin above
its expected monthly peak load in the winter and 16% in summer months to identify when
it should acquire new capacity. With these planning metrics, Avista's first long-term short
position begins in 2030 as shown in Figure 3. Most of the 2030 shortfall is due to an
assumed retirement of the 66 MW Northeast Combustion Turbines (CTs) in Spokane,
Washington.
Avista Corp 2025 Electric IRP 5

Executive Summary
Figure 2: 2026 Generating Capability by Fuel Source
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Natural Gas
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Figure 3: January Peak Load and Resource Position
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Avista Corp 2025 Electric IRP 6

Executive Summary
To address capacity deficits Avista anticipates issuing an all-source request for proposals
(RFP) in May 2025 to cover future resource shortfalls. The RFP may also bring cost
effective resource options to meet future Washington Clean Energy Transformation Act
(CETA) requirements or take advantage of low-cost energy resource opportunities.
Avista's Preferred Resource Strategy (PRS) attempts to forecast the most cost-effective
resource opportunities to meet Avista's customer needs. Given capacity needs are small
until the mid-2030s, the resource strategy does not anticipate large resource acquisitions
immediately unless the energy market is insufficient, loads grow, or early acquisition
benefits from tax credits.
Avista serves both Washington and Idaho customers, but resource policies differ between
the two jurisdictions. Avista balances this difference by selecting resources in the IRP
based on the state driving the resource need. Short run capacity deficits are driven by
Idaho's capacity needs, but in the long run, Washington's CETA policy drives most of the
resource selection. Avista currently allocates resources and costs based on each state's
load allocation, where approximately 2/3 of the generation is assigned to Washington and
1/3 is assigned to Idaho. The divergence where Idaho's resource selection prefers natural
gas CTs and wind, while Washington's strategy selects only clean energy resources,
challenges actual resource acquisition to ensure cost recovery without separating the
system into two. Due to this resource divergence, and the plan being based on generic
resources, actual resource acquisitions may differ from this plan.
As reflected in Table 1 below, in the first 10 years of the plan, market reliance is
anticipated for smaller capacity needs in 2026 to 2028. Avista proposes using the energy
market in this period due to the small shortfall. In the meantime, Avista intends to begin
both direct load control and rate-based demand response (DR) programs.2 The next
resource is distributed solar using Washington State's community solar grants, the
selection include a project each year throughout this IRP as a method to ensure an
equitable transition to clean energy for Washington's Highly Impacted Communities and
Vulnerable Populations, jointly referred to as Named Communities. The first utility scale
resource acquisition begins in 2029 with wind followed by a natural gas CT in 2030. Avista
anticipates a majority of the early resource additions throughout the first 10 years to be
857 MW of wind to take advantage of the Inflation Reduction Act (IRA) incentives to cover
minor resource adequacy needs and set up the utility to have enough clean energy
resources further out in the plan.
2 Demand response capacity amounts are for the 2045 potential. These programs are expected to ramp
over time as customers sign up to participate.
Avista Corp 2025 Electric IRP 7

Executive Summary
Table 1: Preferred Resource Strategy in MW of Capability (2026 to 2035)
Market 39 4 10 - - - - - - - n/a
Regional Transmission Expansion - - - 300 300
Natural Gas CT 90 - 90
NW Wind 200 200 100 - 157 657
Montana Wind - - 100 100 - 200
Distributed Solar 0.5 0.6 0.6 0.7 0.8 0.8 1.0 0.5 0.5 6
Demand Response(Pricing) 14 - - 3 - - - - - 6 23
Demand Response(DLC) 10 3 13
Annual Total (Excludes Market) 25 1 1 203 291 201 101 458 1 9 1,290
Later in the plan (Table 2 showing the 2036 to 2045 PRS), Avista's resource needs grow
due to rapid load growth and resource retirements. In this period, Avista will continue to
invest in DR and distributed solar but will also need to rely on new technologies to meet
capacity requirements using non-greenhouse gas emitting resources, including ammonia
and hydrogen-based fuels via power to gas processes, long duration energy storage, and
nuclear energy. Avista also sees a future in supplementing its 2045 clean energy targets
with solar paired with energy storage, biomass, and geothermal. The 568 MW of wind in
the last 10 years includes replacing expiring wind power purchase agreements (PPA) at
the Palouse and Rattlesnake Flat Wind facilities. The 185 MW of natural gas CTs are the
lowest cost resource to meet Idaho's capacity deficits. In 2045, changes to current
facilities will be integral in meeting Washington's clean energy objectives. The first is co-
firing hydrogen produced using clean energy blended with natural gas at Coyote Springs
2, a 320 MW natural gas facility capable of co-firing 30% hydrogen. The second change
is upgrading the existing Kettle Falls biomass generator and adding a second unit.
New transmission is integral to meeting Avista's future needs. Between Avista's 10-year
system assessment and this IRP, new transmission is needed to access markets and to
integrate new load and generation. The IRP identifies a regional effort to develop a
transmission path between Colstrip, Montana and North Dakota via a DC intertie.
Currently being developed by Grid United, the North Plains Connector would be an
economically viable option to assist in meeting long-term capacity requirements. This plan
includes 300 MW of this new transmission capacity beginning in 2032. New transmission
upgrades will also be needed to integrate proposed resources selected in PRS, including
upgrades between Spokane and North Idaho, and access to energy markets. Other major
transmission projects proposed include the addition of the Blue Bird — Garden Springs
230 kV substation in west Spokane, upgrading the Colstrip transmission system in
Montana, and upgrading the Lolo-Oxbow line between Avista and Idaho Power.
Avista Corp 2025 Electric IRP 8

Executive Summary
Table 2: Preferred Resource Strategy in MW of Capability (2036 to 2045)
Natural Gas CT - - - - 90 - 95 - - - 185
NW Wind - - - - - 140 - 120 108 200 568
Distributed Solar 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.6 5
Utility-Scale Solar - - - - - - - 180 120 - 300
4-hr Batteries 90 60 150
Long Duration Energy Storage 26 85 111
Power to Gas CT(Ammonia) 90 210 300
Hydrogen co-fire at Coyote Springs 2 - 94 94
Biomass 68 68
Geothermal 20 20
Nuclear 100 100
Demand Response(Pricing) 3 4 - 7
Demand Response(DLC) 2 20 - 6 - 11 7 - 45
Annual Total 1 1 5 21 185 146 305 402 322 568 1,954
Avista evaluated 25 potential resource scenarios to understand how the resource portfolio
may change under differing future assumptions. Highlights from the scenario analysis
include:
• 4-hour battery energy storage is the least cost resource to meet immediate
capacity needs absent market acquisitions due to short resource development
timelines.
• Significant nuclear energy, energy storage, and solar will be required in the high
load scenarios due to the limited ability to add other resources due to limited
existing transmission and the high cost to build new transmission.
• Avista's wind acquisition strategy depends on the availability of low-cost sites
without significant transmission interconnect costs, but these sites could be
obtained by other utilities and may lessen Avista ability to acquire lower cost
resources.
• Avista does not need additional clean energy resources to comply with CETA until
the mid-2030s. Due to IRA incentives and expectations of high wholesale electric
prices, acquiring wind generation prior to physical need is economically beneficial
to customers due to the ability to sell the power on the wholesale market, however
wind acquisition could be delayed if pricing of future projects is higher than the
energy market forecast.
• Natural gas resources are the lowest cost capacity resource for Idaho customers
so long as transmission and fuel transportation (or fuel storage) can be available
(or constructed).
• Solar is less favored compared to wind due to the low wholesale market price
forecast in the middle of the day driven by the abundance of other utilities pursuing
solar.
• The resource adequacy targets utilities should plan for in IRPs remains uncertain,
but regional solutions such as the Western Resource Adequacy Program (WRAP)
could reduce Avista's cost to meet resource adequacy on its own. Even if higher
Avista Corp 2025 Electric IRP 9

Executive Summary
resource targets are preferred, the cost impact of additional capacity is
manageable.
From this IRP, Avista has identified several Actions Items to undertake as it moves to the
next plan. First, Avista will be working with interested parties in Washington State to
develop its Clean Energy Implementation Plan (CEIP) for 2026 to 2029. This plan will be
filed October 1 , 2025. Beyond the CEIP, Avista has the following goals:
• Determine the Northeast CTs retirement date and develop a plan for replacing the
lost capacity.
• Pursue transmission expansion opportunities within Avista's service territory and
those connecting with Avista's transmission system.
• Develop an all-source Request for Proposal (RFP) in 2025 for the new resources
needed to meet future capacity deficiencies and determine if the renewable energy
identified in the PRS is cost effective. The RFP will request proposals for demand
response opportunities.
• Investigate options to increase natural gas availability for existing and potential
natural gas generation.
Avista Corp 2025 Electric IRP 10

Table of Contents
Table of Contents
1. Introduction .......................................................................................................25
IRPProcess............................................................................................................... 25
Washington IRP Report Requirements...................................................................... 28
Idaho Regulatory Requirements ................................................................................ 39
Summary of Changes from the 2023 IRP ..................................................................44
2025 IRP Chapter Outline..........................................................................................46
2025 IRP Appendices ................................................................................................47
2. Preferred Resource Strategy............................................................................49
Distributed Energy Resource Selections.................................................................... 50
Supply-Side Resource Selections.............................................................................. 56
Air Emissions Forecast .............................................................................................. 69
RiskAssessment ....................................................................................................... 74
Cost and Rate Projections ......................................................................................... 77
ResiliencyMetrics...................................................................................................... 79
ModelingProcess ...................................................................................................... 81
AvoidedCost.............................................................................................................. 83
3. Economic and Load Forecast .......................................................................... 89
Medium-term Economic & Load Forecast.................................................................. 89
Long-Term Load Forecast........................................................................................ 103
LoadForecast.......................................................................................................... 109
Load Scenario Analysis ........................................................................................... 112
4. Existing Supply Resources ............................................................................ 117
Spokane River Hydroelectric Developments............................................................ 119
Clark Fork River Hydroelectric Development........................................................... 120
Thermal Resources.................................................................................................. 121
Small Avista-Owned Solar ....................................................................................... 124
Power Purchase and Sale Contracts ....................................................................... 124
Resource Environmental Requirements and Issues ................................................ 128
5. Resource Need Assessment .......................................................................... 137
Capacity Requirements............................................................................................ 137
EnergyRequirements .............................................................................................. 143
Forecasted Temperature & Precipitation Analysis ................................................... 145
Washington State Renewable Portfolio Standard .................................................... 149
Washington State's Clean Energy Transformation Act ............................................ 149
Reserves and Flexibility Assessment....................................................................... 152
Natural Gas Pipeline Analysis.................................................................................. 155
6. Distributed Energy Resource Options........................................................... 157
Avista Corp 2025 Electric IRP 11

Table of Contents
EnergyEfficiency ..................................................................................................... 157
DemandResponse .................................................................................................. 165
Distributed Generation Resources........................................................................... 174
DER Evaluation Methodology.................................................................................. 176
DERPotential Study ................................................................................................ 178
Named Communities Investment Fund.................................................................... 181
Other Company Initiatives........................................................................................ 183
7. Supply-Side Resource Options...................................................................... 185
New Resource Options ............................................................................................ 185
UpgradeOpportunities............................................................................................. 204
Qualifying Capacity Credits (QCC) .......................................................................... 205
Non-Energy Impacts ................................................................................................ 206
8. Transmission & Distribution Planning ..........................................................209
Avista Transmission System.................................................................................... 209
Transmission Planning Requirements and Processes............................................. 211
System Planning Assessment.................................................................................. 212
Generation Interconnection......................................................................................214
Future Transmission Projects Under Consideration.................................................216
Distribution Resource Planning................................................................................218
Merchant Transmission Rights.................................................................................223
9. Market Analysis ...............................................................................................225
ElectricMarketplace................................................................................................. 226
Western Interconnect Loads .................................................................................... 227
Generation Resources............................................................................................. 231
Generation Operating Characteristics......................................................................233
Electric Market Price Forecast.................................................................................246
ScenarioAnalyses ...................................................................................................252
10. Portfolio Scenario Analysis............................................................................255
LoadScenarios........................................................................................................ 256
Resource Availability................................................................................................ 256
Other........................................................................................................................ 256
LoadScenarios........................................................................................................257
Resource Availability Scenarios........................................ .................264
......................
OtherPortfolios........................................................................................................272
Reliability Analysis Summary................................................................................... 281
Cost & Rate Impact Summary.................................................................................. 282
Greenhouse Gas Emission Comparison.................................................................. 289
Market Price Sensitivities......................................................................................... 291
11. Action Items..................................................................................................... 319
Avista Corp 2025 Electric IRP 12

Table of Contents
2023 IRP Action Items ............................................................................................. 319
2025 IRP Action Items ............................................................................................. 322
Washington Clean Energy Action Plan ................................................................... 325
Introduction .............................................................................................................. 325
A. Lowest Reasonable Cost..................................................................................... 328
B. Energy Efficiency................................................................................................. 328
C. Equity and Customer Benefits............................................................................. 329
D. Resource Adequacy............................................................................................ 339
E. Demand Response & Load Management Programs ........................................... 340
F. Clean Energy Acquisitions................................................................................... 341
G. Transmission & Distribution................................................................................. 343
H. Alternative Compliance & Social Cost of Greenhouse Gas................................. 346
Customer Benefit Indicator Analysis ........................................................................ 348
Avista Corp 2025 Electric IRP 13

Table of Contents
Table of Figures
Figure 2.1: Energy Efficiency Annual Forecast..........................................................................51
Figure 2.2: Energy Efficiency Savings Programs by Share of Total...........................................52
Figure 2.3: Washington Annual Achievable Potential Energy Efficiency (GWh).........................53
Figure 2.4: Total Demand Response by State and Year in Winter.............................................55
Figure 2.5: System Winter Capacity Load & Resources............................................................64
Figure 2.6: System Summer Capacity Load & Resources.........................................................64
Figure 2.7: System Annual Energy Load & Resources..............................................................65
Figure 2.8: CETA Hourly Analysis.............................................................................................68
Figure 2.9: System and State Clean Energy Ratios Compared to Load ....................................71
Figure 2.10: Avista System Greenhouse Gas Emissions ..........................................................72
Figure 2.11: System Greenhouse Gas Emissions Intensity.......................................................73
Figure 2.12: Avista Owned and Controlled Generating Plant Air Emissions ..............................74
Figure 2.13: Projected Revenue Requirement and Rate Forecast by State...............................78
Figure 2.14: Resource Diversity (Winter Capacity)....................................................................80
Figure 2.15: Resource Diversity (Summer Capacity).................................................................81
Figure 2.16: Washington Energy Efficiency Avoided Cost.........................................................84
Figure 2.17: Idaho Energy Efficiency Avoided Cost...................................................................85
Figure 3.1: MSA Population Growth and U.S. Recessions, 1971-2023 .....................................90
Figure 3.2: Avista and U.S. MSA Population Growth, 2012-2023..............................................91
Figure 3.3: Avista's MSA Non-Farm Employment Breakdown by Major Sector, 2023 ...............92
Figure 3.4: Avista and U.S. Non-Farm Employment Growth, 2012-2023...................................93
Figure 3.5: MSA Personal Income Breakdown by Major Source, 2022 .....................................94
Figure 3.6: Avista and U.S. MSA Real Personal Income Growth...............................................94
Figure 3.7: Forecasting IP Growth.............................................................................................98
Figure 3.8: Industrial Load and Industrial (IP) Index..................................................................98
Figure 3.9: Population Growth vs. Customer Growth, 2002-2023............................................100
Figure 3.10: Forecasting Population Growth ...........................................................................101
Figure 3.11: Change in Energy Use by End Use, 2025-2045..................................................107
Figure 3.12: Washington Residential Gas Heating Market Transformation..............................108
Figure 3.13: Idaho Residential Gas Heating Market Transformation .......................................109
Figure 3.14: History and Forecast Peak Loads........................................................................111
Figure 3.15: History and Forecast Annual Energy Demand.....................................................112
Figure 3.16: Scenario Comparison of Annual Energy (aMW) ..................................................113
Figure 3.17: Scenario Comparison of Winter Peak (MW)........................................................114
Figure 3.18: Scenario Comparison of Summer Peak (MW).....................................................115
Figure 4.1: 2026 Annual Energy Capability (System)..............................................................118
Figure 4.2: 2026 Avista System Seasonal Capability ..............................................................118
Figure 4.3: Avista's Washington State Fuel Mix Disclosure.....................................................119
Figure 5.1: Maintenance Adjustment for Capacity Planning ....................................................141
Figure 5.2: Winter One-Hour Peak Capacity Load and Resources Balance............................142
Figure 5.3: Summer One-Hour Peak Capacity Load and Resources Balance.........................142
Figure 5.4: Energy Contingency Assumption ..........................................................................144
Figure 5.5: Monthly Average Temperature RCP 8.5, RCP 4.5, and Actual 2020-24................147
Figure 5.6: Comparison of Recent 30-Year, and RCP 4.5 Generation ....................................148
Figure 5.7: Washington State CETA Compliance Position ......................................................152
Figure 5.8: Flexible Reserves Required by VER Future ..........................................................153
Figure 5.9: Avista Firm Natural Gas Pipeline Rights................................................................156
Figure 6.1: Historical Conservation Acquisition (System) ........................................................158
Figure 6.2: Analysis Approach Overview.................................................................................159
Avista Corp 2025 Electric IRP 14

Table of Contents
Figure 6.3: Jurisdiction Supply Curves....................................................................................162
Figure 6.4: Program Characterization Process........................................................................167
Figure 6.5: Avista's Net Metering Generation (aMW) ..............................................................174
Figure 6.6: Connected Communities Timeline.........................................................................184
Figure 7.1: Energy Storage Upfront Capital Cost versus Duration...........................................194
Figure 7.2: Lithium-ion Capital Cost Forecast .........................................................................196
Figure 7.3: Wholesale Green Hydrogen Costs per Kilogram ...................................................198
Figure 8.1: Avista Transmission System .................................................................................209
Figure 8.2: Avista 230 kV Transmission System .....................................................................210
Figure 8.3: NERC Interconnection Map...................................................................................212
Figure 9.1: NERC Interconnection Map...................................................................................226
Figure 9.2: 20-Year Annual Average Western Interconnect Load Forecast.............................228
Figure 9.3: Cumulative Resource Retirement Forecast...........................................................232
Figure 9.4: Western Generation Resource Additions (Nameplate Capacity) ...........................233
Figure 9.5: 2025 IRP Henry Hub Natural Gas Price Forecast..................................................234
Figure 9.6: Henry Hub Natural Gas Price Forecast .................................................................236
Figure 9.7: Henry Hub Nominal 20-Year Nominal Levelized Price Distribution........................236
Figure 9.8: Northwest Hydro Generation Comparison.............................................................238
Figure 9.9: Northwest Expected Energy..................................................................................238
Figure 9.10: Carbon Price Assumptions..................................................................................242
Figure 9.11: U.S. Western Interconnect Generation................................................................243
Figure 9.12: Northwest Generation .........................................................................................243
Figure 9.13: 2022 and 2045 Greenhouse Gas Emissions .......................................................244
Figure 9.14: Greenhouse Gas Emissions Forecast.................................................................245
Figure 9.15: Northwest Regional Greenhouse Gas Emissions Intensity..................................246
Figure 9.16: Mid-Columbia Electric Price Forecast Range ......................................................247
Figure 9.17: Winter Average Hourly Electric Prices (December— February) ...........................250
Figure 9.18: Spring Average Hourly Electric Prices (March —June)........................................250
Figure 9.19: Summer Average Hourly Electric Prices (July - September)................................251
Figure 9.20: Autumn Average Hourly Electric Prices (October— November)...........................251
Figure 9.21: Change in Henry Hub Natural Gas Prices ...........................................................252
Figure 9.22: Mid-Columbia Nominal Levelized Prices Scenario Analysis ................................253
Figure 9.23: Mid-Columbia Annual Electric Price Scenario Analysis .......................................254
Figure 10.1: 2043-2045 Washington Electrification Cost.........................................................262
Figure 10.2: PVRR Summary..................................................................................................284
Figure 10.3: Washington Energy Rate Comparison ................................................................285
Figure 10.4: Idaho Energy Rate Comparison ..........................................................................286
Figure 10.5: System Cost versus Risk Comparison ................................................................287
Figure 10.6: Portfolio PVRR with Risk Analysis.......................................................................288
Figure 10.7: 2045 System Energy Cost with Risk....................................................................289
Figure 10.8: Emission Reduction (Millions of Metric Tons (2045 compared to 2026)...............290
Figure 10.9: Change in Emissions Compared to Portfolio PVRR ............................................291
Figure 1: 10-Year Cost Effective Conservation Potential Assessment.....................................329
Figure 2: Washington Service Area Named Communities.......................................................337
Figure 3: Spokane Named Communities.................................................................................338
Figure 4: Clarkston Area Named Communities .......................................................................338
Figure 5: Social Cost of Greenhouse Gas Prices ....................................................................348
Figure 6: Planning Process.....................................................................................................351
Figure 7: WA Customers with Excess Energy Burden (Before Energy Assistance).................353
Figure 8: Average Washington Customer Excess Energy Burden...........................................354
Figure 9: Total MWh of DER in Named Communities..............................................................355
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Table of Contents
Figure 10: Named Community Investment and Benefits..........................................................356
Figure 11: Planning Reserve Margin.......................................................................................357
Figure 12: Generation in Washington and/or Connected to Avista Transmission ....................358
Figure 13: Washington Located Air Emissions........................................................................359
Figure 14: Washington Direct and Net Emissions ...................................................................360
Figure15: Job Creation...........................................................................................................361
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Table of Contents
Table of Tables
Table 1.1: TAC and Public Meeting Dates and Agenda Items...................................................26
Table 1.2: External Technical Advisory Committee Participating Organizations ........................28
Table 1.3: Timing and Plan Horizon ..........................................................................................28
Table 1.4: Load Forecast Requirements ...................................................................................28
Table 1.5: Distributed Energy Resource Requirements.............................................................29
Table 1.6: Supply-Side Resource Requirements.......................................................................30
Table 1.7: Renewable Resource Integration Requirements ......................................................30
Table 1.8: Regional Generation and Transmission Requirements.............................................30
Table 1.9: Resource Evaluation Requirements .........................................................................31
Table 1.10: Resource Adequacy Requirements........................................................................31
Table 1.11: Economic, Health, & Environmental Burdens & Benefits Requirements .................31
Table1.12: Load Forecast ........................................................................................................31
Table 1.13: Portfolio Analysis and Preferred Portfolio Requirements ........................................32
Table 1.14: Clean Energy Action Plan.......................................................................................33
Table 1.15: Avoided Cost and Nonenergy Impact Requirements ..............................................34
Table 1.16: Data Disclosure Requirements...............................................................................35
Table 1.17: Information from Qualifying Facilities Requirements...............................................35
Table 1.18: Report of Substantive Changes Requirements.......................................................35
Table 1.19: Summary of Public Comments Requirements ........................................................35
Table 1.20: Policy Statement Concerning IRA and IIJA in the IRP............................................36
Table 2.1: Biennial Conservation Target for Washington Energy Efficiency ..............................53
Table 2.2: Demand Response Selection ...................................................................................55
Table 2.3: Thermal Resource Portfolio Exit Assumptions..........................................................57
Table 2.4: Resource Selections (2026-2035) ............................................................................59
Table 2.5: PRS Resource Selections (2036-2045)....................................................................60
Table 2.6: Reliability Metrics .....................................................................................................66
Table 2.7: 2045 Hourly Analysis................................................................................................69
Table 2.8: Idaho New Resource Avoided Costs........................................................................87
Table 2.9: Washington New Resource Avoided Costs ..............................................................88
Table 3.1: UPC Models Using Non-Weather Driver Variables...................................................97
Table 3.2: Customer Growth Correlations, 1998-2023 ..............................................................99
Table 3.3: Overview of Avista Analysis Segmentation Scheme...............................................104
Table 3.4: Overview of Avista Analysis Segmentation Scheme...............................................106
Table 3.5: Expected Case Energy and Peak Forecasts ..........................................................110
Table 3.6: Incremental Difference between Expected Case and Scenario in 2045..................115
Table 4.1: Avista-Owned Hydroelectric Resources .................................................................121
Table 4.2: Avista-Owned Thermal Resources.........................................................................122
Table 4.3: Avista-Owned Thermal Resource Capability ..........................................................122
Table 4.4: Avista-Owned Solar Resource Capability...............................................................124
Table 4.5: Mid-Columbia Capacity and Energy Contracts .......................................................125
Table 4.6: Columbia Basin Hydro Projects..............................................................................126
Table 4.7: PURPA Agreements...............................................................................................126
Table 4.8: Net PURPA Agreements........................................................................................127
Table 4.9: Other Contractual Rights and Obligations ..............................................................128
Table 4.10: Avista Owned and Controlled PM Emissions........................................................135
Table 5.1: 2030 Resource Adequacy Study............................................................................140
Table 5.2: Monthly Energy Evaluation Methodologies.............................................................143
Table 5.3: Net Energy Position................................................................................................145
Table 5.4: Comparison of Temperature Increases by RCP .....................................................146
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Table of Contents
Table 5.5: Hydro Generation Forecast Comparison (aMW).....................................................148
Table 5.6: Washington State EIA Compliance Position Prior to REC Banking (aMW).............149
Table 5.7: CETA Compliance Target Assumptions .................................................................150
Table 5.8: VER Study Results.................................................................................................154
Table 5.9: Top Five Historical Peak Day Natural Gas Usage (Dekatherms)............................155
Table 6.1: Cumulative Potential Savings (Across All Sectors for Selected Years)...................161
Table 6.2: Demand Response Program Options by Market Segment .....................................168
Table 6.3: DR Program Steady-State Participation Rates (% of Eligible Customers) ..............172
Table 6.4: System Program Cost and Potential.......................................................................173
Table 6.5: Avista-Owned Solar Resource Capability...............................................................175
Table 6.6: DER Generation & Storage Options Size and Cost................................................176
Table 6.7: DER Cost and Benefit Impacts...............................................................................177
Table 6.8: Summary Results for 2045, Reference Scenario....................................................179
Table 6.9: NCIF Spending by Category...................................................................................181
Table 7.1: Natural Gas-Fired Plant Levelized Costs................................................................190
Table 7.2: Natural Gas-Fired Plant Cost and Operational Characteristics...............................190
Table 7.3: Forecasted Solar and Wind Capital Cost ($/kW).....................................................192
Table 7.4: Forecasted Solar and Wind O&M ($/kW-yr.)...........................................................192
Table 7.5: Levelized Solar and Wind Prices ($/MWh)..............................................................192
Table 7.6: Levelized Cost for Lithium-Ion Storage at a Solar Facility ($/kW-month) ................193
Table 7.7: Pumped Hydro Options Cost ($/kW-month)............................................................195
Table 7.8: Lithium-Ion Levelized Cost ($/kW-month)...............................................................196
Table 7.9: Storage Levelized Cost ($kW-month).....................................................................197
Table 7.10: Hydrogen Based Resource Option Costs.............................................................200
Table 7.11: Qualifying Capacity Credit for Certain Resources.................................................205
Table 7.12: IRP Resource NEI Values ....................................................................................207
Table 8.1: New Generation Sites - Integration Cost Estimates................................................215
Table 8.2: Existing Generation Sites - Integration Cost Estimates...........................................215
Table 8.3: Third-Party Large Generation Interconnection Requests........................................216
Table 8.4: Existing Generator (Top 10 Feeders) .....................................................................219
Table 8.5: Merchant Transmission Rights ...............................................................................224
Table 9.1: Aurora Zones .........................................................................................................227
Table 9.2: January through June Load Area Correlations .......................................................229
Table 9.3: July through December Load Area Correlations.....................................................230
Table 9.4: Area Load Coefficient of Determination (Standard Deviation/Mean).......................230
Table 9.5: Area Load Coefficient of Determination (Standard Deviation/Mean).......................231
Table 9.6: Natural Gas Price Basin Differentials from Henry Hub............................................235
Table 9.7: Nominal Levelized Flat Mid-Columbia Electric Price Forecast................................247
Table 9.8: Annual Average Mid-Columbia with CCA Electric Prices ($/MWh) .........................248
Table 9.9: Annual Average Mid-Columbia without CCA Electric Prices ($/MWh).....................249
Table 10.1: Scenario List ........................................................................................................256
Table 10.2: Low and High Load Growth Scenarios .................................................................257
Table 10.3: RCP 8.5 Temperatures for Winter Planning..........................................................259
Table 10.4: Electrification Scenarios .......................................................................................261
Table 10.5: Large Load Impacts..............................................................................................263
Table 10.6: Northeast CT Analysis..........................................................................................265
Table 10.7: On-System Wind Limitations ................................................................................266
Table 10.8: No Regional Transmission ...................................................................................267
Table 10.9: No Power to Gas Resources................................................................................268
Table 10.10: No IRA Impacts ..................................................................................................269
Table 10.11: No Power to Gas Resources..............................................................................270
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Table of Contents
Table 10.12: 2045 Clean Resource Portfolio...........................................................................272
Table 10.13: Counterfactual Scenarios ...................................................................................274
Table 10.14: Resource Adequacy Scenarios ..........................................................................275
Table 10.15: Maximum Washington Customer Benefits..........................................................276
Table 10.16: 2045 Customer Benefits Indicator Results..........................................................277
Table 10.17: CETA Target Scenarios......................................................................................277
Table 10.18: CETA 2045 Cost Cap Scenario..........................................................................280
Table 10.19: CCA Repealed Scenario ....................................................................................281
Table 10.20: Reliability Results...............................................................................................282
Table 10.21: Jurisdiction Cost and Rate Summary..................................................................283
Table 10.22: Jurisdiction PVRR Sensitivity Analysis ...............................................................292
Table 10.23: PVRR and Emission Changes............................................................................292
Table 10.24: Portfolio #1: Preferred Resource Strategy..........................................................293
Table 10.25: Portfolio #2: Alternative Lowest Reasonable Cost..............................................294
Table 10.26: Portfolio #3: Baseline..........................................................................................295
Table 10.27: Portfolio #4: Clean Resource Portfolio................................................................296
Table 10.28: Portfolio #5: Low Load Forecast.........................................................................297
Table 10.29: Portfolio #6: High Load Forecast ........................................................................298
Table 10.30: Portfolio #7: Washington Building Electrification.................................................299
Table 10.31: Portfolio #8: WA Building and Transportation Electrification ...............................300
Table 10.32: Portfolio #9: System Building and Transportation Electrification .........................301
Table 10.33: Portfolio #10: Washington Max Customer Benefits.............................................302
Table 10.34: Portfolio #11: 500 MW of Nuclear in 2040 ..........................................................303
Table 10.35: Portfolio #12: 17% PRM .....................................................................................304
Table 10.36: Portfolio #13: 30% PRM .....................................................................................305
Table 10.37: Portfolio #14: Power to Gas Unavailable ............................................................306
Table 10.38: Portfolio #15: Minimum CETA Target .................................................................307
Table 10.39: Portfolio #16: Maximum CETA Target ................................................................308
Table 10.40: Portfolio #17: PRS Cost Cap Constrained ..........................................................309
Table 10.41: Portfolio #18: Data Center Load (200 MW in 2030) ............................................310
Table 10.42: Portfolio #19: RCP 8.5 Temperatures for Load...................................................311
Table 10.43: Portfolio #20: System Bldg & Transportation Electrification- RCP 8.5.................312
Table 10.44: Portfolio #21: No Regional Transmission............................................................313
Table 10.45: Portfolio #22: Retire Northeast in 2026...............................................................314
Table 10.46: Portfolio #23: 200 MW Wind Limit.......................................................................315
Table 10.47: Portfolio #24: No IRA Tax Incentives..................................................................316
Table 10.48: Portfolio #25: Northeast Retires in 2035 .............................................................317
Table 10.49: Portfolio #26: No Climate Commitment Act.........................................................318
Table 1: Resource Acquisition Forecast..................................................................................325
Table 2: Clean Energy Load and Resource Balance (aMW) ...................................................327
Table 3: Cumulative Demand Response (MW) .......................................................................340
Table 4: Wind Selections (MW)...............................................................................................342
Table 5: Alternative Compliance .............................................................................................347
Table 6: Customer Benefit Indicators ......................................................................................349
Avista Corp 2025 Electric IRP 19

Acronym List
Acronym List
ADSS: Avista's Decision Support System
AEG: Applied Energy Group
aMW: Average Megawatt(s)
ARAM: Avista Reliability Assessment Model
BCP: Biennial Conservation Plan
CAIDI: Customer Average Interruption Duration Index
CCA: Climate Commitment Act
CEMI: Customer Experiencing Multiple Interruptions
CBO: Community Based Organizations
CCA: Climate Commitment Act
CC&B: Customer Care and Billing
CDD: Colling Degree Day
CEAP: Clean Energy Action Plan
CEIP: Clean Energy Implementation Plan
CETA: Clean Energy Transformation Act
CBI: Customer Benefit Indicator
CPA: Conservation Potential Assessment
CPI: Consumer Price Index
CT: Combustion Turbine
CCCT: Combined Cycle Combustion Turbine
CTA: Consumer Technology Association
DER: Distributed Energy Resource
DOE: Department of Energy
DOH: Department of Health
DPAG: Distribution Planning Advisory Group
DR: Demand Response
EAG: Equity Advisory Group
EAAG: Energy Assistance Advisory Group
Avista Corp 2025 Electric IRP 20

Acronym List
EEAG: Energy Efficiency Advisory Group
EIA: Energy Independence Act
ELCC: Equivalent Load Carrying Capability
ERWH: Electric Resistance Water Heater
EUE: Expected Unserved Energy
EUI: Energy Use Index
EV: Electric Vehicle
FERC: Federal Energy Regulatory Commission
FSP: Forward Showing Program
H2: Hydrogen
HDD: Heating Degree Day
HG: Mercury
IAQ: Indoor Air Quality
IOU: Investor-Owned Utility
IP: Industrial Production Index of the U.S. Federal Reserve
IPCC: Intergovernmental Panel on Climate Change
IRP: Integrated Resource Plan
GHG: Greenhouse Gas
GISS: Goddard Institute for Space Studies
GWh: Gigawatt-hour(s)
HRSG: Heat Recovery Steam Generator
LDC: Local Distribution Center
LGIR: Large Generation Interconnection Request
LOLE: Loss of Load Expectation
LOLEV: Loss of Load Expected Events
LOLH: Loss of Load Hours
LOLP: Loss of Load Probability
MIP: Mixed Integer Program
MISO: Mid-Continent Independent System Operator
MSA: Metropolitan Statistical Area
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Acronym List
MW: Megawatt(s)
MWh: Megawatt-hour(s)
NC: Named Community
NCIF: Named Community Investment Fund
NEEA: Northwest Energy Efficiency Alliance
NEI: Non-Energy Impact
NOx: Nitrous Oxide
NREL: National Renewable Energy Laboratory
OASIS: Open Access Same-time Information System
O&M: Operations and Maintenance
P2G: Power to Gas
PPA: Power Purchase Agreement
PRiSM: Preferred Resource Strategy Model
PRM: Planning Reserve Margin
PRS: Preferred Resource Strategy
PT: Production Tax (ratio)
PUD: Public Utility District
PURPA: Public Utility Regulatory Policies Act
QCC: Qualifying Capacity Credit
QF: Qualifying Facility
RA: Resource Adequacy
RAP: Real Average Energy Price
RCP: Representative Concentration Pathway
RCW: Revised Code of Washington
RFP: Request for Proposal
RMJOC: River Management Joint Operating Committee
SBCC: State Building Code Council
SCR: Selective Catalytic Reduction
SMR: Small Modular Reactor
SO2: Sulfur Dioxide
Avista Corp 2025 Electric IRP 22

Acronym List
SPP: Southwest Power Pool
T&D: Transmission and Distribution
TAC: Technical Advisory Committee
TE: Transportation Electrification
TEP: Transportation Electrification Plan
TOU: Time of Use (Rates)
TRC: Total Resource Cost
UCT: Utility Cost Test
UEC: Unit Energy Consumption
UPC: Use Per Customer
UTC: Washington Utilities and Transportation Commission
VOC: Volatile Organic Compounds
VER: Variable Energy Resource
WAC: Washington Administrative Code
WECC: Western Electricity Coordinating Council
WPP: Western Power Pool
WRAP: Western Resource Adequacy Program
Avista Corp 2025 Electric IRP 23

Acronym List
This Page is Intentionally Left Blank
Avista Corp 2025 Electric IRP 24

Chapter 1: Introduction
1 . Introduction
Avista is a multijurisdictional utility serving electric in Washington and Idaho and natural
gas customers in Washington, Idaho, and Oregon. Each state has its own rules and
regulations regarding filing dates, content, and methods used to develop electric
integrated resource plans. Avista works diligently to consolidate the different state
requirements into one plan filed every other year.
The energy planning requirements between Avista's two electric jurisdictions take
different approaches to planning. Idaho focuses on reliability and serving customers with
the lowest cost resources. Washington's energy policy focuses on the lowest reasonable
cost while transitioning the economy to cleaner energy resources through the Clean
Energy Transformation Act (CETA), Climate Commitment Act (CCA) and other related
policies. These requirements change how resource planning is approached, the modeling
techniques and assumptions being used, and requires careful consideration and
implementation of many new issues going well beyond the traditional utility planning
requirements of safety, reliability, and lowest cost. These three pillars of resource
planning have not gone away and still need to be met along with the new requirements
and aspirations. Some of these new requirements will take several iterations to determine
how to plan for and implement them while still meeting the traditional planning
requirements.
Washington requires clean energy use and development to meet CETA's 100% clean
energy goals, additional emphasis on health and equity issues, promoting more diverse
participation in the planning process, and disincentives for greenhouse gas emitting
resources. These disincentives include the end of coal-fired plants serving Washington
customers by 2026 and the tapering down of the use of natural gas-fired plants as CETA
gets closer to its 100% clean energy goal in 2045.
This chapter discusses the IRP requirements for Idaho and Washington, the process used
to develop the IRP, where each of the requirements can be found, changes from the 2023
IRP, and concludes with an overview of the chapters and appendices included.
IRP Process
This IRP includes a series of public meetings with a mix of technical experts, such as
commission staff, regional utility professionals, project developers, advocacy groups,
environmental groups, interested state agencies, and both commercial and residential
customers. Table 1.1 lists the dates and topics covered in each of the public meetings
with assumptions and concepts used in the creation of this IRP. The meetings included
discussions about:
Avista Corp 2025 Electric IRP 25

Chapter 1: Introduction
• how loads are expected to be served between 2026 and 2045 and the
resources already in place to serve current and future needs,
• the operating and environmental costs and benefits of new resources,
• the costs and benefits of energy efficiency measures and demand
response,
• different types of energy storage,
• the expected future and alternate futures, and
• the estimated non-energy impacts of resource decisions.
All these issues combined with the assumptions made and how each are included in the
analysis are discussed. The subsequent results of the modeling provide an expectation
of future prices for different resources, energy efficiency, demand response, and energy
storage options can be evaluated against. Avista develops a preferred portfolio of
resources as a roadmap to serving future needs. There are also less technical public
meetings for customers and others who are interested in hearing about the plan and
providing comments.
cable 1.1: TAC and Public ""-pting Dates and Agenda Items
Meeting Date Agenda Items
TAC 1 — September 26, 2023 • CEIP Update
• TAC Process and Methods Proposals
• PLEXOS Overview and Back Cast Analysis
• Available Resource Options Discussion
• Work Plan
TAC 2 Equity Focus—January 30, 0 How Avista Includes Equity Principles
2024 • Customer Benefit Indicators
• How Avista Practices Equity Outcomes
• Equity Planning in the IRP
TAC 3— March 21, 2024 • Review of January Cold Weather Event
• Wholesale Price Forecasts— Natural Gas and Electric
• Portfolio and Market Scenario Options
TAC 4—April 9, 2024 0 Future Climate Analysis
• Economic Forecast& Five-Year Load Forecast
TAC 5—April 23, 2024 0 Long Run Load Forecast
• Load Forecast Comparison
• Review Planned Scenario Analysis
TAC 6— May 7, 2024 0 Conservation Potential Assessment
• Demand Response Potential Assessment
TAC 7— May 21, 2024 • Variable Energy Resources Study
• Portfolio/Market Scenarios
TAC 8—June 4, 2024 0 Electrification Scenarios
• New Resource Options Costs and Assumptions
• 2030 Loss of Load Probability Stud
TAC 9—June 18, 2024 0 Load & Resources Discussion
• IRP Generation Option Transmission Planning Studies
• Distribution Planning and Microgrids
Avista Corp 2025 Electric IRP 26

Chapter 1: Introduction
Technical Modeling Workshop— . PRiSM Model Tour
June 25, 2024 . New Resource Cost Model
• ARAM Model Tour
TAC 10 —July 16, 2024 . Preferred Resource Strategy Results
• Resource Adequacy
• Washington Customer Benefit Indicator Impacts
• Resiliency Metrics
TAC 11 —July 30, 2024 . Connected Communities Program Update
• Avista — Spokane Tribe Energy Resiliency Partnership
Update
• Preferred Resource Strategy Results
• Avoided Costs
• Remaining TAC Schedule & Scenario Planning
TAC 12 —August 13, 2024 . Preferred Resource Strategy Results
• Avoided Costs
TAC 13 —September 17, 2024 . Energy Efficiency Update
• Scenario Analysis
Virtual Public Meetings— Natural . Recorded Presentation
Gas and Electric IRPs— November . Morning Comment and Question Session
13, 2024 . Daytime Comment and Question Session
Avista greatly appreciates the valuable contributions and time commitments made by
each of its TAC members and wishes to acknowledge and thank the organizations and
members who participated in the development of this IRP. Table 1.2 lists organizations
participating in the 2025 IRP TAC process.
Avista Corp 2025 Electric IRP 27

Chapter 1: Introduction
Table 1.2: External Technical Advisory Committee Participating Organizations
Organization
Avan rid National Grid
Applied Energy Group Northwest LECET
Biomethane, LLC NW Energy Coalition
Bonneville Power Administration Northwest Laborers
Building Industry Association of Washington Northwest Power and Conservation Council
California Hydronics Corporation Pacific NW Utilities Conference Committee
City of Spokane Phil Jones Consulting
Clearwater Paper Puget Sound Energy
Clearway Energy Pullman City Council
Creative Renewable Solutions Renewable Northwest
DNV Residential and Small Commercial Customers
Energy Keepers Inc. Sapere Consulting
Form Energy Sun2o Partners
Fortis BC Tollhouse Energy
Gail Head Development Utilicom Consulting Group
Grant County PUD Wartsila Energy
Grid United Washington SEIA
Idaho Power Washington State Office of the Attorney General
Idaho Public Utilities Commission Washington State Department of Enterprise
Services
Invenergy Washington State University
LIUNA Washington Utilities and Transportation
Commission
Mitsubishi Power Americas White Gull Analytics
Myno Carbon Whitman County Commission
Sun2o Partners
Washington IRP Report Requirements
This IRP satisfies the requirements for the content of an IRP defined in WAC 480-100-
620 and the minimum requirements under WAC 480-100-620(2-17) include the following
shown in Tables 1 .3 through 1.18:
Table 1.3: Timing and Plan Hori7nn
WAC 480-100-620(2) Load Forecast Chapter 3— Economic and Load Forecast
Table 1.4• ' d Forecast Requirements
WAC 480-100-620(2) The IRP must include a range of forecasts of Chapter 3—
projected customer demand that reflect the effect Economic and
of economic forces on the consumption of Load Forecast
electricity and address changes in the number,
type, and efficiency of end uses of electricity.
Avista Corp 2025 Electric IRP 28

Chapter 1: Introduction
Table 1.5: Distributed Energy Resource Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100- The IRP must include assessments of a variety of Chapter 3-
620(3)(a) distributed energy resources. These assessments Economic and
must incorporate nonenergy costs and benefits not Load Forecast
fully valued elsewhere within any integrated
resource plan model. Utilities must assess the Chapter 6—
effect of distributed energy resources on the Distributed Energy
utility's load and operations under Resources
RCW 19.280.030 (1)(h). The commission strongly
encourages utilities to engage in a distributed
energy resource planning process as described in
RCW 19.280.100. If the utility elects to use a
distributed energy resource planning process, the
IRP should include a summary of the results.
WAC 480-100- (i) Energy efficiency and conservation potential Chapter 2- PRS
620(3)(b)(i-iv) assessment—The IRP must assess currently
employed and potential policies and programs Chapter 6—
needed to obtain all cost-effective conservation, Distributed Energy
efficiency, and load management improvements, Resources
including the ten-year conservation potential used
in calculating a biennial conservation target under Appendix N-
chapter 480-109 WAC; Energy Burden
(ii) Demand response potential assessment—The Assessment
IRP must assess currently employed and new
policies and programs needed to obtain all cost-
effective demand response;
(iii) Energy assistance potential assessment—The
IRP must include distributed energy programs and
mechanisms identified pursuant to
RCW 19.405.120, which pertains to energy
assistance and progress toward meeting energy
assistance need; and
(iv) Other distributed energy resource potential
assessments—The IRP must assess other
distributed energy resources 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 distributed energy resources
on the utility's load and operations.
Avista Corp 2025 Electric IRP 29

Chapter 1: Introduction
Table 1.6: Supply-Side Resource Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100-620(4) The IRP must include an assessment of a wide Chapter 7 —
range of commercially available generating and Supply-Side
nonconventional resources, including ancillary Resource Options
service technologies.
Appendix G —
Public Input and
Results Data
Table 1.7: Renewable resource Integration Requirements
0
WAC 480-100-620(5) An assessment of methods, commercially Chapter 7—
available technologies, or facilities for integrating Supply-Side
renewable resources including, but not limited to, Resource Options
battery storage and pumped storage, and
addressing overgeneration events, if applicable to
the utility's resource portfolio. The assessment
may address ancillary services.
Table 1.8: Regional Generation and Transmission Requirements
WAC 480-100- The IRP must include an assessment of the Chapter 8—
620(6)(a) availability of regional generation and transmission Transmission
capacity on which the utility may rely to provide Planning &
and deliver electricity to its customers. Distribution
(a)The assessment must include the utility's
existing transmission capabilities, and future
resource needs during the planning horizon,
including identification of facilities necessary to
meet future transmission needs.
WAC 480-100-620- (b)The assessment must also identify the general Chapter 8—
(6)(b) location and extent of transfer capability limitations Transmission &
on its transmission network that may affect the Distribution
future siting of resources. Planning
Appendix D—
Transmission &
Distribution
Assessments
Appendix J — New
Resource
Transmission
Table
Avista Corp 2025 Electric IRP 30

Chapter 1: Introduction
Table 1.9: Resource Evaluation Requirements
DiscussionWAC Rule Requirement IRP
WAC 480-100-620(7) The IRP must include a comparative evaluation of Chapter 2 all identified resources and potential changes to Preferred
existing resources for achieving the clean energy Resource Strategy
transformation standards in WAC 480-100-610 at
the lowest reasonable cost. Chapter 10-
Scenario Analysis
Table 1.10: Resource Adequacy Requirements
DiscussionWAC Rule Requirement IRP
WAC 480-100-620(8) The IRP must include an assessment and Chapter 2—
determination of resource adequacy metrics. It Preferred
must also identify an appropriate resource Resource
adequacy requirement and measurement metrics Strategv
consistent with
RCW 19.405.030 through 19.405.050.
Table " " Economic, Health, & Environmental Burdens & Benefits Requirements
DiscussionWACM Requirement IRP
WAC 480-100-620(9) The IRP must include an assessment of energy and Clean Energy
nonenergy benefits and reductions of burdens to Action Plan
vulnerable populations and highly impacted
communities; long-term and short-term public
health and environmental benefits, costs, and risks;
and energy security risk. The assessment should
be informed by the cumulative impact analysis
conducted by the department of health.
Table 1.12: Load Forecast
DiscussionWAC Rule Requirement AJ11111WF__ IRP
WAC 480-100- The IRP must include a range of possible future Chapter 10 —
620(10)(a) scenarios and input sensitivities for the purpose of Portfolio
testing the robustness of the utility's resource Scenarios
portfolio under various parameters. The IRP must
also provide a narrative description of scenarios Chapter 3- Load
and sensitivities the utility used, including those Forecast
informed by the advisory group process.
(a)At least one scenario must describe the
alternative lowest reasonable cost and reasonably
available portfolio that the utility would have
implemented if not for the requirement to comply
with RCW 19.405.040 and 19.405.050, as
described in WAC 480-100-660(1). This scenario's
conditions and inputs should be the same as the
preferred portfolio except for those conditions and
inputs that must change to account for the impact of
RCW 19.405.040 and 19.405.050.
Avista Corp 2025 Electric IRP 31

Chapter 1: Introduction
WAC 480-100- At least one scenario must be a future climate Chapter 3-
620(10)(b) change scenario. This scenario should incorporate Economic and
the best science available to analyze impacts Load Forecast
including, but not limited to, changes in snowpack,
streamflow, rainfall, heating and cooling degree Chapter 5-
days, and load changes resulting from climate Resource Needs
change. Assessment
Chapter 10—
Portfolio
Scenarios
WAC 480-100- At least one sensitivity must be a maximum Chapter 10—
620(10)(c) customer benefit scenario. This sensitivity should Portfolio
model the maximum amount of customer benefits Scenarios
described in RCW 19.405.040(8) prior to balancing
a ainst other goals.
Table 1.13: Portfolio Analysis and Preferred Portfolio Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100- The utility must integrate the demand forecasts and Chapter 2—
620(11)(a) resource evaluations into a long-range integrated Preferred
resource plan solution describing the mix of Resource
resources that meet current and projected resource Strategy
needs. Each utility must provide a narrative
explanation of the decisions it has made, including
how the utility's long-range integrated resource plan
expects to:
(a)Achieve the clean energy transformation
standards in WAC 480-100-610 (1) through (3) at
the lowest reasonable cost;
WAC 480-100- Serve utility load, based on hourly data, with the Chapter 2 —
620(11)(b) output of the utility's owned resources, market Preferred
purchases, and power purchase agreements, net of Resource
any off-system sales of such resource; Strateciv
WAC 480-100- Include all cost-effective, reliable, and feasible Chapter 6—
620(11)(c) conservation and efficiency resources, using the Distributed
methodology established in RCW 19.285.040, and Energy
demand response; Resources
WAC 480-100- Consider acquisition of existing renewable Included as part
620(11)(d) resources; of future RFP
analysis
WAC 480-100- In the acquisition of new resources constructed after Included as part
620(11)(e) May 7, 2019, rely on renewable resources and of future RFP
energy storage, insofar as doing so is at the lowest analysis
reasonable cost;
WAC 480-100- Maintain and protect the safety, reliable operation, Chapter 5-
620(11)(f) and balancing of the utility's electric system, Resource Needs
including mitigating over-generation events and Assessment
achieving the identified resource adequacy
requirement;
Avista Corp 2025 Electric IRP 32

Chapter 1: Introduction
WAC 480-100- Achieve the requirements in WAC 480-100- Clean Energy
620(11)(g)(i and ii) 610 (4)(c); the description should include, but is not Action Plan
limited to:
(i) The long-term strategy and interim steps the utility
will take to equitably distribute benefits and reduce
burdens for highly impacted communities and
vulnerable populations; and
(ii) The estimated degree to which benefits will be
equitably distributed and burdens reduced over the
planning horizon.
620(11)(h) Assess the environmental health impacts to highly Clean Energy
impacted communities; Action Plan
620(11)(i) Analyze and consider combinations of distributed Chapter 6-
energy resource costs, benefits, and operational Distributed
characteristics including ancillary services, to meet Energy
system needs; and Resources
620(11)0) Incorporate the social cost of greenhouse gas Chapter 2-
emissions as a cost adder as specified in Preferred
RCW 19.280.030(3). Resource
Strategy
Clean Energy
Action Plan
Table 1.14: Clean Energy Action Plan
WAC Rule Requirement IRP Discussion
WAC 480-100- The utility must develop a ten-year clean energy Clean Energy
620(12)(a) action plan for implementing Action Plan
RCW 19.405.030 through 19.405.050. The CEAP
must:
(a) Be at the lowest reasonable cost;
WAC 480-100- Identify and be informed by the utility's ten-year cost- Chapter 6—
620(12)(b) effective conservation potential assessment as Distributed
determined under RCW 19.285.040; Energv
Resources
Appendix C —
AEG
Conservation
and DR
Assessments
WAC 480-100- Identify how the utility will meet the requirements in Clean Energy
620(12)(c)(i— iii) WAC 480-100-610 (4)(c) including, but not limited to: Action Plan
(i) Describing the specific actions the utility will take
to equitably distribute benefits and reduce burdens
for highly impacted communities and vulnerable
populations;
(ii) Estimating the degree to which such benefits will
be equitably distributed and burdens reduced over
the CEAP's ten-year horizon; and
Avista Corp 2025 Electric IRP 33

Chapter 1: Introduction
(iii) Describing how the specific actions are
consistent with the long-term strategy described in
WAC 480-100-620 11
WAC 480-100- Establish a resource adequacy requirement; Clean Energy
620(12)(d) Action Plan
Chapter 5
Resource Needs
Assessment
WAC 480-100- Identify the potential cost-effective demand Chapter 6—
620(12)(e) response and load management programs that may Distributed
be acquired; Energy
Resources
WAC 480-100- Identify renewable resources, nonemitting electric Clean Energy
620(12)(f) generation, and distributed energy resources that Action Plan
may be acquired and evaluate how each identified
resource may reasonably be expected to contribute
to meeting the utility's resource adequacy
requirement;
WAC 480-100- Identify any need to develop new, or to expand or Clean Energy
620(12)(g) upgrade existing, bulk transmission and distribution Action Plan
facilities;
WAC 480-100- Identify the nature and possible extent to which the Clean Energy
620(12)(h) utility may need to rely on an alternative compliance Action Plan
option identified under RCW 19.405.040 (1)(b), if
appropriate; and
WAC 480-100- Incorporate the social cost of greenhouse gas Clean Energy
620(12)(i) emissions as a cost adder as specified in Action Plan
RCW 19.280.030 3 .
Table 1.15: Avoided Cost and Nonenergy Impact Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100- The IRP must include an analysis and summary of Chapter 2 —
620(13) the avoided cost estimate for energy, capacity, Preferred
transmission, distribution, and greenhouse gas Resource
emissions costs. The utility must list nonenergy Strategy
costs and benefits addressed in the IRP and should
specify if they accrue to the utility, customers, Appendix K-
participants, vulnerable populations, highly impacted Schedule 62
communities, or the general public. The utility may
provide this content as an appendix.
Avista Corp 2025 Electric IRP 34

Chapter 1: Introduction
Table 1.16: Data Disclosure Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100- The utility must include the data input files made Appendix G—
620(14) available to the commission in native format per Public Input and
RCW 19.280.030 (10)(a) and (b) and in an easily Results Data
accessible format as an appendix to the IRP. For
filing confidential information, the utility may Appendix H —
designate information within the data input files as Confidential
confidential, provided that the information and Inputs and
designation meet the requirements of WAC 480-07- Models
160.
Table 1.17: Information from Qualifying Facilities Requirements
Reg&2MML IRP Discussion
WAC 480-100- Each utility must provide information and analysis Chapter 2 —
620(15)(a) that it will use to inform its annual filings required Preferred
under chapter 480-106 WAC. The detailed analysis Resource
must include, but is not limited to, the following Strategy
components:
(a)A description of the methodology used to Appendix K-
calculate estimates of the avoided cost of energy, Schedule 62
capacity, transmission, distribution and emissions
averaged across the utility; and
WAC 480-100- Resource assumptions and market forecasts used in Chapter 9-
620(15)(b) the utility's schedule of estimated avoided cost Market Analysis
required in WAC 480-106-040 including, but not
limited to, cost assumptions, production estimates, Appendix G-
peak capacity contribution estimates and annual Public Input and
capacity factor estimates. Results Data
Table 1.18: Report of Substantive Changes Requirements
WAC Rule RequiremerwL IRP Discussion
WAC 480-100- The IRP must include a summary of substantive Chapter 1 —
620(16) changes to modeling methodologies or inputs that Introduction,
result in changes to the utility's resource need, as Involvement and
compared to the utility's previous IRP. Process Changes
Table 1.19: Summary of Public Comments Requirements
WAC Rule Requirement IRP Discussion
WAC 480-100- The utility must provide a summary of public Appendix M —
620(2) comments received during the development of its IRP Public Comments
and the utility's responses, including whether issues
raised in the comments were addressed and
incorporated into the final IRP as well as
documentation of the reasons for rejecting any public
input. The utility may include the summary as an
appendix to the final IRP. Comments with similar
content or input may be consolidated with a single
utility response
Avista Corp 2025 Electric IRP 35

Chapter 1: Introduction
Policy Statement for IRA and IIJA Funding in IRPs
Table 1.20 shows how this IRP conforms with the UTC's expectations and preferences
regarding the incorporation of the Inflation Reduction Act (IRA) and the Infrastructure
Investment and Jobs Act of 2021 (IIJA) in the IRP in Docket U-240013.
Table 1.9n- Policy Statement Concerning IRA and IIJA in the IRP
Expectation IRP Discussion
Utilities are expected to update IRP cost assumptions to Chapter 7—Supply Side
include the extended ITC and PTC tax credits through the Resource Options
current expiration date, incorporate the "bonus" creditsl5
where appropriate, and include sensitivity analysis for varying Appendix G: Supply Side
level of program uptake (e.g., electric vehicle adoption, Resource Options.xlsm
distributed energy resources, building electrification, energy
efficiency, etc.). Chapter 3: Economic and Load
This includes natural gas utilities reflecting the impact of Forecast
these federal funding dollars that may promote electrification
into their load forecasts.
While we recognize the rebate programs for electric utilities This will be addressed in the CIEP
are more difficult to forecast, scenarios should be included to
evaluate a high, medium, and low uptake to better inform
project selection downstream during development of the
utilities' CEIPs, and the following procurement and
acquisition processes when data from rebate programs
becomes available.
Additionally, we expect electric utilities to identify and Chapter 8 Transmission Planning
evaluate transmission needs that may qualify for IRA & Distribution
transmission-related programs. We also encourage utilities to
evaluate alternative options such as clean repowering and Clean Energy Action Plan
reconductorin .
Further, utilities should include an index within the IRP to Table 1.20 Policy Statement
notate where IRA and IIJA opportunities are included within Concerning IRA and IIJA in the
its analysis. We believe the public benefit of documenting this IRP
information to facilitate review by the Commission, advisory
groups, and other interested persons outweighs the burden
the requirement may impose on utilities.
Finally, utilities are encouraged to review the RMI publication, Noted
"Planning to Harness the Inflation Reduction Act:A Toolkit for
Regulators to Ensure Resource Plans Optimize
Federal Funding,"as 2025 IRPs are under development.
Washington Clean Energy Implementation Plan (CEIP) Coordination
The IRP, in accordance with WAC 480-100-625 (4)(c), updates any elements in the
utility's current CEIP as described in WAC 480-100-640. Avista's 2021 CEIP was
approved with Conditions in June 2022. Avista has included the inputs used and approved
in the development of the 2021 Clean Energy Action Plan (CEAP)filed with the 2021 IRP.
In addition, Conditions agreed to as part of the approval of the 2021 CEIP in Docket UE-
210628 are included in the modeling informing this IRP. The following assumptions were
used to develop the clean energy requirements for 2030 and 2045 CETA requirements.
Avista Corp 2025 Electric IRP 36

Chapter 1: Introduction
• Qualifying clean energy is determined by procurement and delivery of
clean energy to Avista's system for all years.
• The clean energy goal is applied to retail sales less in-state Public
Utility Regulatory Policies Act (PURPA) generation constructed prior
to 2019 plus voluntary renewable energy programs.
• Customer voluntary Renewable Energy Credits (REC) programs do
not qualify toward the CETA standard.
• Primary compliance generation includes:
• Washington's share of legacy hydro generation (defined the facility is
operating or contracted with deliveries before 2022).
• All wind, solar, and biomass generation. Nonpower attributes
associated with Idaho's share may be purchased by Washington,
• Newly acquired or contracted non-emitting generation including hydro,
wind, solar, or biomass.
• Avista may transfer qualifying clean energy allocated to the Idaho
jurisdiction to Washington by compensating Idaho at market REC
prices.
• Avista is not planning to use Idaho's share of legacy hydro prior to
2030 for compliance. After 2030, these resources are planned to be
available for Alternative Compliance.
Conditions For IRP Progress Report from the CEIP
Several of the Washington Utilities and Transportation Commission's (WUTC) approved
conditions for the Company's CEIP were required to be included in the 2023 Progress
Report. The following six conditions, listed by their original number issued in Order 01
from the WUTC, are covered in the 2023 Progress Report and if applicable updated in
this 2025 IRP.
(2) Avista will apply Non-Energy Impacts (NEIs) and Customer Benefit Indicators (CBIs)
to all resource and program selections in determining its Washington resource strategy,
in its 2023 IRP/Progress Report and will incorporate any guidance given by the
Commission on how to best utilize CBIs in CEIP planning and evaluation. Avista agrees
to engage and consult with its applicable advisory groups (IRP Technical Advisory
Committee (TAC) and Energy Efficiency Advisory Group (EEAG)) regarding an
appropriate methodology for including NEIs and CBIs in its resource selection. (Per Order
01: Avista will consult with its Equity Advisory Group (EAG) after the development of this
methodology to ensure the methodology does not result in inequitable results.)
Avista discussed with the TAC and EEAG on Oct 11, 2022, its approach to using
both NEI and CBIs with the progress report, The EAG was also consulted during
its meetings held on November 161" and 18th, 2022. Members did not voice
concerns pertaining to inequities in the Company's approach.
Avista Corp 2025 Electric IRP 37

Chapter 1: Introduction
(8) Avista in its IRP resource selection model for the 2023 IRP Progress Report will give
the model the option to meet Clean Energy Transformation Act (CETA) goals with a
choice between an Idaho allocated existing renewable resource at market price (limited
to Kettle Falls, Palouse Wind, Rattlesnake Flat, Chelan PUD purchase contracts 2 & 3 or
acquiring a new 100% allocated Washington renewable resource for primary compliance.
Further, the model will have the option to acquire new 100% allocated resource, market
REC, or Idaho allocated REC (at market prices) to meet alternative compliance.
Avista included logic in the PRISM model to choose how it solves to meet primary
and alternative compliance requirements either by using existing resources or by
acquiring new resources.
(14) Avista will include a Distributed Energy Resources (DERs) potential assessment for
each distribution feeder no later than its 2025 electric IRP. Avista will develop a scope of
work for this project no later than the end of 2022, including input from the IRP TAC,
EEAG, and Distribution Planning Advisory Group (DPAG). The assessment will include a
low-income DER potential assessment. Avista will document its DER potential
assessment work in the Company's 2023 IRP Progress Report in the form of a project
plan, including project schedule, interim milestones, and explanations of how these efforts
address WAC 480-100-620(3)(b)(iii) and (iv).
The potential assessment for this study was discussed at both the TA and EEAG
meetings in October 2022 during the 2023 Progress Report/IRP process, the
project plan and schedule are described in Chapter 5 and the proposed scope of
work is in Appendix G of the 2023 IRP. The project was completed in 2024, and
the associated report is available in Appendix F of this plan.
(34) For its 2023 IRP Progress Report, Avista commits to reevaluate its resource need
given acquisitions the Company has made since its 2021 IRP (e.g., Chelan PUD hydro
slice contracts) and include those proposed changes in its 2023 Biennial Clean Energy
Implementation Plan (CEIP) Update.
Avista has included within its resource energy need all long-term resources
currently under contract including the Chelan PUD slice agreements and the
Columbia Basin Hydro agreement in the 2023 Progress Report/IRP. Further, it
includes planned upgrades to both Kettle Falls and Post Falls as well as the
extension of the existing Lancaster Purchase Power Agreement (PPA).
After the 2023 Progress Report/IRP was completed, Avista chose to no longer
pursue an upgrade to Kettle Falls upon completion of the 2023 RFP. The Post
Falls project is underway, but upon further evaluation, no additional capacity at the
project is planned under the new project configuration.
Avista Corp 2025 Electric IRP 38

Chapter 1: Introduction
(35)Avista recognizes that not all CBIs will be relevant to resource selection (for example,
some CBIs pertain to program implementation). For its 2023 IRP Progress Report, and
future IRPs and progress reports, Avista should discuss each CBI and where the CBI is
not relevant to resource selection, explain why.
Chapter 11 of the 2023 IRP outlines how each CBI is relevant or not to resource
selection or studied within the resource planning process. For those CBIs with a
relation to resource selection, a forecast of their impact on the plan is included.
The 2025 Clean Energy Action Plan also includes this relevant information.
(36) For its 2023 IRP Progress Report, Avista will:
A. At the September 28, 2022, Electric IRP TAC meeting, present draft supply
side resource cost assumptions, including DERs. The Company commits to
revising said cost assumptions if TAC stakeholder feedback warrants
changes. Avista will update its 2023 Electric IRP Work Plan (UE-200301) to
reflect the date of this TAC meeting.
B. Use the Qualifying Capacity Credit (QCC) for renewable and storage
resources from the Western Power Pool's Western (WPP) Regional
Adequacy Program (WRAP), if available, or explain why the WRAP's QCCs
are inappropriate for use.
C. Update its load forecast to include the baseline zero emission vehicles (ZEV)
scenario from its Transportation Electrification Plan.
Avista presented and provided TAC members with a complete supply resource
assumptions at the September 2022 meeting during the 2023 Progress Report/IRP
process. The resource assumptions are discussed in Chapter 6 of 2023 Progress
Report/IRP, along with associated technical documentation in Appendix F of the
2023 IRP. Avista also uses QCC values where applicable from the WRAP, these
are discussed in Chapter 3 for existing resources, Chapter 5 for DERs, and
Chapter 6 for utility scale resources. Within Chapter 2 is a discussion of the
associated loads included using the Transportation Electrification Plan from the
2023 IRP. The 2025 IRP continues to use the same methodology as the 2023 IRP
with updated assumptions.
Idaho Regulatory Requirements
The IRP process for Idaho has several requirements documented in IPUC Orders Nos.
22299 and 25260. Order 22299 dates back to 1989; this order outlines the requirement
for the utility to file a "Resource Management Report[(RMR)]". This report recognize[s]
the managerial aspects of owning and maintaining existing resources as well as
procuring new resources and avoiding/reducing load. [The Commission's]desire is the
report on the utility's planning status, not a requirement to implement new planning
efforts according to some bureaucratic dictum. We realize that integrated resource
planning is an ongoing, changing process. Thus, we consider the RMR required herein
Avista Corp 2025 Electric IRP 39

Chapter 1: Introduction
to be similar to an accounting balance sheet, i.e., a "freeze-frame"look at a utility's fluid
process.
The report should discuss any flexibilities and analyses considered during comprehensive
resource planning such as:
1. Examination of load forecast uncertainties
2. Effects of known or potential changes to existing resources
3. Consideration of demand- and supply-side resource options
4. Contingencies for upgrading, optioning and acquiring resources at optimum
times (considering cost, availability, lead-time, reliability, risk, etc.) as future
events unfold.
Avista outlines the order's requirements below for ease of readability for each of the
Commission's requirements.
Existing Resource Stack
Identification of all resources by category below;3 including the utility shall provide a copy
of the utility's most recent U.S. Department of Energy Form EIA-714 submittal and the
following specific data, as defined by the NERC, ought to be included as an appendix:4
a) Hydroelectric;
i. Rated capacity by unit;
ii. Equivalent Availability Factor by month for most recent 5 years;
iii. Equivalent Forced Outage Rate by month for most recent 5 years; and
iv. FERC license expiration date.
b) Coal-fired;
i. Rated Capacity by unit;
ii. Date first put into service;
iii. Design plant life (including life extending upgrades, if any);
iv. Equivalent Availability Factor by month for most recent 5 years; and
V. Equivalent Forced Outage Rate by month for most recent 5 years.
c) Oil or Gas fired;
i. Rated Capacity by unit;
ii. Date first put into service;
iii. Design plant life (including life extending upgrades, if any);
iv. Equivalent Availability Factor by month for most recent 5 years; and
V. Equivalent Forced Outage Rate by month for most recent 5 years.
d) PURPA Hydroelectric;
i. Contractual rated capacity;
3 Resources less than three megawatts should be grouped as a single resource in the appropriate
category.
4 FERC Form 714 can be on-line at https://www.ferc.gov/docs-filing/forms/form-714/data.asp
Avista Corp 2025 Electric IRP 40

Chapter 1: Introduction
ii. Five-year historic hours connected to system, by month (if known);
iii. Five-year historic generation (kWh), by month;
iv. Level of dispatchability, if any; and
V. Contract expiration date.
e) PURPA Thermal;
i. Contractual rated capacity;
ii. Five-year historic hours connected to system, by month (if known);
iii. Five-year historic generation (kWh), by month;
iv. Level of dispatchability, if any; and
V. Contract expiration date.
f) Economy Exchanges;
I. For contract purchases & exchanges, key contract terms and conditions
relating to capacity, energy, availability, price, and longevity.
II. For economy purchases and exchanges, 5-year historical monthly average
capacity, energy, and prices.
g) Economy Purchases;
I. For contract purchases & exchanges, key contract terms and conditions
relating to capacity, energy, availability, price, and longevity.
II. For economy purchases and exchanges, 5-year historical monthly average
capacity, energy, and prices.
h) Contract Purchases;
I. For contract purchases & exchanges, key contract terms and conditions
relating to capacity, energy, availability, price, and longevity.
II. For economy purchases and exchanges, 5-year historical monthly average
capacity, energy, and prices.
i) Transmission Resources; and
I. Information useful for estimating the power supply benefits and limitations
appurtenant to the resources in question.
j) Other.
I. Information useful for estimating the power supply benefits and limitations
appurtenant to the resources in question.
Load Forecast
Each RMR should discuss expected 20-year load growth scenarios for retail markets and
for the federal wholesale market including "requirements" customers, firm sales, and
economy (spot) sales. For each appropriate market, the discussion should:
a) identify the most recent monthly peak demand and average energy consumption
(where appropriate by customer class), both firm and interruptible;
b) identify the most probable average annual demand and energy growth rates by
month and, where appropriate, by customer class over at least the next three years
and discuss the years following in more general terms;
Avista Corp 2025 Electric IRP 41

Chapter 1: Introduction
c) discuss the level of uncertainty in the forecast, including identification of the
maximum credible deviations from the expected average growth rates; and
d) identify assumptions, methodologies, databases, models, reports, etc. used to
reach load forecast conclusions.
This section of the report is to be a short synopsis of the utility's present load condition,
expectations, and level of confidence. Supporting information does not need to be
included but should be cited and made available upon request.
Additional Resource Menu
This section should consist of the utility's plan for meeting all potential jurisdictional load
over the 20-year planning period. The discussion should include references to expected
costs, reliability and risks inherent in the range of credible future scenarios.
• An ideal way to handle this section could be to describe the most
probable 20-year scenario followed by comparative descriptions of
scenarios showing potential variations in expected load and supply
conditions and the utility's expected responses thereto. Enough
scenarios should be presented to give a clear understanding of the
utility's expected responses over the full range of possible future
conditions.
• The guidance provided above is intended to ensure maximum
flexibility to utilities in presenting their resource plans. Ideally, each
utility will use several scenarios to demonstrate potential maximum,
minimum and intermediate levels of new resource requirements and
the expected means of fulfilling those requirements. For example,
• A credible scenario requiring maximum new resources might be
regional load growth exceeding 3% per year combined with
catastrophic destruction (earthquake, fire, flood, etc.) of a utility's
largest resource (i.e., Bridger coal plant for IPCo and PP&L, Hunter
coal plant for UP&L and Noxon hydro plant for WWP).
• A credible scenario causing reduced utilization of existing resources
might be regional stagflation combined with loss of a major industry
within a utility's service territory. Analyses of intermediate scenarios
would also be useful.
• To demonstrate the risks associated with various proposed
responses, certain types of information should be supplied to describe
each method of meeting load. For example,
• If new hydroelectric generating plants are proposed, the lead time
required to receive FERC licensing and the risk of license denial
should be discussed.
• If new thermal generating plants are proposed, the size, potential for
unused capacity, risks of cost escalation and fuel security should be
discussed and compared to other types of plants.
• If off-system purchases are proposed, specific supply sources should
be identified, regional resource reserve margin should be discussed
Avista Corp 2025 Electric IRP 42

Chapter 1: Introduction
with supporting documentation identified, potential transmission
constraints and/or additions should be discussed, and all associated
costs should be estimated.
• If conservation or demand side resources are proposed, they should
be identified by customer class and measure, including documentation
of availability, potential market penetration and cost.
• Because existing hydroelectric plants could be lost to competing
companies if FERC relicensing requirements are not aggressively
pursued, relicensing alternatives require special consideration. For
example,
• If hydroelectric plant relicensing upgrades are proposed, their costs
should be presented both as a function of increased plant output and
of total plant output to recognize the potential of losing the entire site.
• Costs of upgrades not required for relicensing should be so identified
and compared only to actual increased capacity/energy availability at
the unit, line, substation, distribution system, or other affected plant.
Increased maintenance costs, instrumentation, monitoring,
diagnostics, and capital investments to improve or maintain availability
should be quantified.
• Because PURPA projects are not under the utility's control, they also
require special consideration. Each utility must choose its own way of
estimating future PURPA supplies. The basis for estimates of PURPA
generation should be clearly described.
Other provisions from Order 22299
• Because the RMR is expected to be a report of a utility's plans, and
because utilities are being given broad discretion in choosing their
reporting format, Least Cost Plans or Integrated Resource Plans
submitted to other jurisdictions should be applicable in Idaho.
• Utilities should use discretion and judgement to determine if reports
submitted to other jurisdictions provide such emphasis, if adding an
appendix would supply such emphasis, or if a separate report should
be prepared for Idaho.
• The project manager responsible for the content and quality of the
RMR shall be clearly identified therein and a resume of her/his
qualifications shall be included as an appendix to the RMR.
• Finally, the Resource Management Report is not designed to turn the
IPUC into a planning agency nor shall the Report constitute pre-
approval of a utility's proposed resource acquisitions.
• The reporting process is intended to be ongoing-revisions and
adjustments are expected. The utilities should work with the
Commission Staff when reviewing and updating the RMRs. When
appropriate, regular public workshops could be helpful and should be
a part of the reviewing and updating process.
• Most parties seem to agree that reducing and/or avoiding peak
capacity load or annual energy load has at least the equivalent effect
Avista Corp 2025 Electric IRP 43

Chapter 1: Introduction
on system reliability of adding generating resources of the same size
and reliability. Furthermore, because conservation almost always
reduces transmission and distribution system loads, most parties
consider reliability effects of conservation superior to those of
generating resources. Consequently, the Commission finds that
electric utilities under its jurisdiction, when formulating resource plans,
should give consideration to appropriate conservation and demand
management measures equivalent to the consideration given
generating resources.
• Therefore, we find that the parties should use the avoided cost
methodology resulting from the No. U-1500-170 case for evaluating
the cost effectiveness of conservation measures. The specific means
for comparing No. U-1500-170 case avoided costs to conservation
costs will initially be developed case-by-case as specific conservation
programs are proposed by each utility. Prices to be paid for
conservation resources procured by utilities are discussed later in this
Order.
• Give balanced consideration to demand side and supply side
resources when formulating resource plans and when procuring
resources.
• Submit to the Commission, no later than March 15, 1989, and at least
biennially thereafter, a Resource Management Report describing the
status of its resource planning as of the most current practicable date.
Order 25260 Requirements
This order documents additional requirements for resource planning including:
• Give full consideration to renewables, among other resource options.
• Investigate and carefully weigh the site-specific potential for particular
renewables in their service area.
• Deviations from the integrated resource plans must be explained. The
appropriate place to determine the prudence of an electric utility's plan
or the prudence of an electric utility's following or failing to follow a
plan will be in general rate case or other proceeding in which the issue
is noticed.
Summary of Changes from the 2023 IRP
Avista's 2025 IRP methodology is similar to the 2023 IRP, but with updated assumptions.
The major assumption changes include capacity and energy position results, updated
energy efficiency and demand response potentials, updates to supply-side resource
options and costs, refreshed wholesale market analysis and additional methods for the
portfolio optimization analysis, each are described below.
Avista Corp 2025 Electric IRP 44

Chapter 1: Introduction
Capacity and Energy Position, Including Load Forecasting
• Avista continues to use the WPP's WRAP methodology for capacity
planning. But uses its own planning reserve margin of 24% in the
winter and 16% in the summer. Avista also uses information from the
WRAP and public reports to estimate resource QCC values.
• Load and hydro forecasts use the Representative Concentration
Pathway (RCP) 4.55 temperature and hydro forecast for future years
rather than historical averages for winter months, Avista uses RCP 8.5
temperatures for summer months.
• Avista did not consider upgrades to Kettle Falls or Post Falls in the
baseline capacity/energy position.
Energy Efficiency and uemana Response
• Demand Response QCC values are credited with the planning reserve
margin value for capacity analysis. This assumes DR is netted prior to
calculating the PRM resulting in additional preference for these
programs.
• Avista evaluated additional electric vehicle load control options.
Supply-Side Resource Optionr
• Avista refined the list of available resources based on potential
technologies being acquired. This includes removing liquid-air storage
and combined flow battery technologies as a generic resource type.
Avista added hydrogen co-firing to Coyote Springs 2 and Rathdrum
CTs.
Market Analysis
• A new regional resource forecast is updated to reflect the latest
available information utilizing Energy Exemplar's latest Western
Electricity Coordinating Council (WECC) database and Avista's
National Consultant's electric forecast.
• The Climate Commitment Act (CCA) is reflected in the market forecast
using Ecology's price estimate for imported power and power plants
without free allowances. Avista assumed the CCA prices will be
included in dispatch decisions for all in-state plants beginning in 2031.
Portfolio Optimization Analysis
• Added a natural gas LDC module with the ability to move natural gas
customers to electric dynamically if cost effective or for a scenario
analysis.
5 RCP 4.5 is defined in Chapter 4.
Avista Corp 2025 Electric IRP 45

Chapter 1: Introduction
2025 IRP Chapter Outline
Chapter 1: Introduction, Involvement and Process Changes
This chapter introduces the IRP, covers requirements and details public participation and
involvement in the process used to develop it, as well as highlighting significant
assumption, modeling and process changes between the 2023 and 2025 IRPs.
Chapter 2: Preferred Resource Strategy
This chapter details the Preferred Resource Strategy (PRS) selection process used to
develop the 2025 PRS and resulting avoided costs.
Lhapter 3: tconomic and Load Forecast
This chapter covers regional economic conditions, Avista's energy and the peak load
forecasts, including scenarios with different load projections.
Chapter 4: Existing Supply Resources
This chapter provides an overview of Avista-owned generating resources and its
contractual resources and obligations and environmental considerations.
Chapter 5: Resource Needs Assessment
This chapter reviews Avista reliability planning and reserve margins, risk planning,
resource requirements and provides an assessment of its reserves and resource
flexibility. This chapter also covers the RCP 4.5 and 8.0 temperature and hydrology
forecasts.
Chapter 6: Distributed Energy Resource Options
This chapter discusses customer focused resources such as energy efficiency programs,
demand response and distributed generation and energy storage. It provides an overview
of the conservation and demand response potential assessments, and customer owned
or other distributed generation resources.
Chapter 7: Supply-Side Resource Options
This chapter covers the cost and operating characteristics of utility scale supply-side
resource options modeled for the 2025 IRP.
.napter u. , ransmission rianning a, Jistribution
This chapter discusses Avista distribution and transmission systems, as well as regional
transmission planning issues. It includes details on transmission cost studies used in IRP
modeling and summarizes Avista's 10-year Transmission Plan. The chapter concludes
with a discussion of distribution planning, including storage benefits to the distribution
system.
Avista Corp 2025 Electric IRP 46

Chapter 1: Introduction
Chapter 9: Market Analysis
This chapter details Avista IRP modeling and its analyses of the wholesale electric and
natural gas markets.
Chapter 10: Scenario Analysis
This chapter presents alternative resource portfolios and shows how each scenario
performs under different energy market conditions.
Chapter 11: Action Plan
This chapter discusses progress made on Action Items in the 2023 IRP. It details the
areas Avista will focus on between publication of this plan and the 2027 IRP.
Clean Energy Action Plan
Avista's 10-year Clean Energy Action Plan (CEAP) is the lowest reasonable cost plan of
resource acquisition given societal costs, clean energy, and reliability requirement targets
over the IRP's 20-year time horizon, including known information and assumptions
regarding the future. This plan describes how Avista will meet the key considerations
required by the UTC. The CEAP is the basis for the 2025 Clean Energy Implementation
Plan (CEIP).
2025 IRP Appendices
Appendix A: TAC and Public Presentations
This appendix includes the presentations for the 14 TAC meetings and meeting notes.
Appendix B: IRP Work Plan
This appendix includes 2025 IRP Work Plan outlining the process Avista's used to
develop its 2025 Electric IRP for filing with the Washington and Idaho Commissions by
January 2, 2025.
Appendix C: AEG Conservation and Demand Response Potential Assessments
This appendix includes the conservation (energy efficiency) and demand response
potential assessment studies completed by AEG for Avista's service territory including
the measure list of program options.
Appendix D: 10-Year Transmission/ Distribution Plan
This appendix includes Avista's 10-year System Plan and the transmission and
distribution system assessment reports.
Appendix E: Transmission Generation Integration Study
This appendix includes the assessment of cost and system changes to integrate resource
opportunities onto Avista's transmission system resource option study results.
Avista Corp 2025 Electric IRP 47

Chapter 1: Introduction
Appendix F: Distributed Energy Resources Study
This appendix includes the study results for the feeder level potential of distributed energy
resources for the Washington service territory and the forecasting methodology reports.
Appendix G: Public Input and Results Data
This appendix includes modeling input data including: CCA prices, load forecast, natural
gas prices, social cost of carbon, and resource option costs. It includes the named
community maps, the PRiSM models for resource selection, and the electric market price
forecast. Energy Efficiency avoided cost calculations.
Appendix H: Confidential lnr)uts and Model
This appendix including the Aurora model, ARAM models for resource adequacy, and the
Hourly CETA analysis.
Appendix I: Historical Generation Operation Data (Confidential)
This confidential appendix includes actual monthly data for PURPA generation and forced
outage data for Avista resources.
Appendix J: New Resource Table for Transmission
This appendix approximates the potential location of new resources for transmission
planning.
Appendix K: Washington State Schedule 62 (Partially Confidential)
This appendix includes the proposed rates and confidential supporting files and avoided
cost calculations for small PURPA generators qualifying for Schedule 62.
Appendix M: Public CommentE
This appendix includes written comments from the public and advisory group members.
Appendix N: Enerav Burden Assessment
This appendix includes Avista's energy burden assessment performed by Empower
Dataworks per WAC 480-100-620(3)(iii).
Avista Corp 2025 Electric IRP 48

Chapter 2: Preferred Resource Strategy
2. Preferred Resource Strategy
The IRP starts with Avista's current resource position and projected load growth. The
Preferred Resource Strategy (PRS) is mix of new generation, storage, demand response,
market purchases, and energy efficiency options to meet load growth in a safe, reliable,
cost-effective, and equitable manner as reasonably possible. The PRS must also meet
state and federal policy goals, such as Washington's clean energy and reduced
greenhouse gas (GHG) emissions goals. The resource strategy is not a specific action
plan, but it does guide what types of resources Avista may pursue to meet load growth
while honoring regulatory and policy requirements. The actual acquisition of new
resources will use a Request for Proposal (RFP) process or other market opportunities to
obtain the needed resources.
Section Highlights
• Energy efficiency meets 32% of future load growth; the biennial energy
efficiency target for 2026-2027 is 55% higher than the 2024-2025 target.
• Demand Response reduces system peak load 4% by 2045.
• Wind generation may be acquired as early as 2029 if it benefits customers
to acquire the resource early.
• Avista's capacity position may drive the need for new resources earlier if
loads increase faster than forecasted.
• Transmission interconnect and capacity limits could decrease future
generation acquisition and may drive alternative resource choices rather
than preferred options.
• Meeting Washington's 2045 clean energy targets will require a diversified
clean capacity portfolio using emerging technologies such as small
modular reactors, power-to-gas (ammonia/hydrogen) fueling combustion
turbines, and long-duration energy storage technologies.
The procurement of supply-side resources will be through energy market transactions
and a competitive bidding process with energy suppliers. This IRP shows resource
owners and developers the timing, size, and types of resources most applicable for
procurement. Avista expects this process may result in a different resource mix compared
with the one presented in this chapter once real projects are known. Lastly, the IRP helps
determine the avoided costs of serving future loads and shows how external forces and
policies impact the utility's resource mix. Avista will use this strategy to inform its
Washington Clean Energy Implementation Plan (CEIP) for 2026 through 2029; however,
the ultimate action plan approved by the Commission for this period may differ from this
plan.
The PRS uses the best available information at the time of the analyses, including Avista's
interpretation of Washington's Clean Energy Transformation Act (CETA) requirements.
CETA's "use rules" determine how renewable energy will qualify as either "primary" or
Avista Corp 2025 Electric IRP 49

Chapter 2: Preferred Resource Strategy
"alternative" compliance to the 2030 greenhouse neutral standard. The IRP utilizes a
least-cost planning methodology with specific social cost impacts specified by
Washington's requirements such as the social cost of greenhouse gas (SCGHG) and
Non-Energy Impacts (NEI). Due to divergent Idaho and Washington state energy policies,
Avista separates the two jurisdictions for this plan by creating an individual resource plan
as needed for each state while adding shared system resources where possible.
Although, actual resource acquisitions are not separated by jurisdiction at this time.
Avista's PRS describes the lowest reasonable cost resource mix considering risk, given
Avista's needs for new capacity, energy, and clean or non-carbon emitting resources for
each state, while accounting for social and economic factors prescribed by Washington
State policies. The PRS includes supply-side resources, distributed energy resource
(DER) options, energy efficiency, and demand response (DR) to serve customer loads.
The plan compares resource options to find the lowest-cost portfolio considering the non-
power costs/benefits (such as NEls) to meet seasonal capacity deficits, annual energy
needs, and CETA requirements. The analysis considers a minimum spending threshold
using the Named Communities Investment Fund (NCIF)6 to enhance the equitable
transition to clean energy in Washington's Named Communities. The Idaho portion of the
plan utilizes a least cost methodology without societal cost estimates.
Distributed Energy Resource Selections
Energy Efficiency Selections
Energy efficiency savings meets 32% of future load growth in this plan. However, new
loads, including electric transportation and building electrification, will outpace energy
efficiency adoption limiting energy efficiency's ability to minimize load growth. Without
electrification, energy efficiency could keep future load growth flat. Avista's load forecast
(described in Chapter 3) is net of future energy efficiency savings. Avista adds back the
selected quantity of efficiency savings to the load forecast through an iterative technique
in the Preferred Resource Strategy Model (PRiSM) until the amount of energy efficiency
selected netted from the load equals the load forecast. This evaluation considers over
3,000 energy efficiency measures and individually models each program's capacity and
energy contributions to rigorously evaluate each program's benefit to the system. This
method ensures an accurate accounting of peak savings.
Over the planning horizon, energy efficiency programs will reduce 870 cumulative
gigawatt-hours of energy sales between 2026 and 2045. When considering the reductions
of transmission and distribution losses by energy efficiency, loads are 105 aMW less with
these programs. Figure 2.1 shows total energy and peak hour savings by state for both
winter and summer. Winter peaks are reduced by nearly 183 MW and summer peaks are
reduced by approximately 149 MW. Over the IRP planning horizon, 26% of energy
6 The NCIF was proposed in Avista's 2021 CEIP and commits to spend up to$5 million annually on specific
actions in Named Communities.
Avista Corp 2025 Electric IRP 50

Chapter 2: Preferred Resource Strategy
efficiency comes from Idaho customers and 74% from Washington customers.
Washington has more energy efficiency savings relative to its 65% share of total load due
to its higher avoided costs driven by CETA and other policies, such as including societal
benefits in the economic evaluation.
rigure 2.1. energy Efficiency Annual Forecast
1,000 200
�WA-GWh
900 180
�ID-GWh
800 -Winter Peak(MW) 160
Summer Peak(MW)
700 140
i
600 120 w
3F
R
600 100
3 tM
d
p 400 80 2
300 60
200 40
100 20
00 h 00 O O N CO V LO CO Ih 00 O CD CO 'IT LO
N N N N rM M co Cl) (M M co rM (+7 M 7 7 V V 7 V
O O O O O O O O O O O C. O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Commercial customers deliver 59% of the total energy efficiency savings, followed by
residential customers (33%), with the remainder from industrial customers. Of the total
savings, low-income households provide 16% of the energy efficiency savings and
receive benefits at zero or minimal customer cost. The greatest sources of energy
efficiency, at 68%, are from lighting and space heating/cooling measures. Figure 2.2
shows the program type by share of the total percentage of savings through 2045. Idaho
has fewer program types due to lower avoided costs triggering fewer programs overall,
while Washington's higher avoided costs identify more programs as cost effective.
Avista separately analyzes energy efficiency programs for low-income households
compared to other households. This allows Avista to include non-energy impacts for
Washington's lower income customers to increase savings potential. By 2045, 22% of
Washington's energy savings is from low-income households or 15.7 aMW of energy
savings.
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Chapter 2: Preferred Resource Strategy
Figure 2.2: Energy Efficiency Savings ProgI dMb by Share of Total
Lighting 36.1 /°° 55.7%
Space Heating/Cooling 23.8% °
32.4/°
Water Heating0 4'4% °
10.7/°
Ventilation 7.9%
W7.2%
Refrigeration 2.6%
3.2/°
Appliances . 3.9�%
3.8/°
Pumping 0.1%°
2.3/° ■Idaho
Miscellaneous 1.0%
1.7% ■Washington
Motors 0.0%
1.4%
Process 0.0%
1 0.7/o
Food Preperation 0.6°%
0.4/°
Electronics 0.0%
0.1 /°
Washinaton Biennial Conservation Plan
The amount of energy efficiency the PRS identifies leads to specific programs in
Washington and Idaho. To meet Washington's Energy Independence Act (EIA)
requirements, the IRP determines cost-effective solutions and potential new programs for
business planning, budgeting, and program development. Pursuant to Washington
requirements, the biennial conservation target must be no lower than a pro rata share of
the utility's ten-year conservation potential. In setting Avista's target, both the two-year
achievable potential and the ten-year pro rata savings are determined with the higher
value used to inform the EIA biennial target. Figure 2.3 shows the annual selection of new
energy efficiency in Washington compared to the 10-year pro-rata share methodology.
The 2026-2027 achievable potential identified by the Conservation Potential Assessment
(CPA) is 58,873 MWh for Washington although the pro-rata share of the ten-year potential
is 73,672 MWh. The target exceeds the achievable potential by nearly 14,799 MWh over
the two-year period. The pro-rata target is higher than the two-year potential as savings
occurring later in the 10-year period as compared to the first two years of the plan
increases the target. Avista will have a challenge to identify and acquire this additional
energy efficiency. Table 2.1 outlines Avista's biennial target of 73,672 MWh and includes
Avista Corp 2025 Electric IRP 52

Chapter 2: Preferred Resource Strategy
adjustments for NEEA and decoupling. This biennial target is 55% higher than the 2024-
25 goal of 47,635 MWh.
'figure 2.3: Washington Annual Achievable Potential Energy Efficiency (GWh)
400
368
350 Selected EE 332
—10-Yr Pro Rata Share 295
300
258
N
250 0 221
x
V 200 184
147
T 150
� 111
100 74
50 37
0
2026 2027 2028 2029 2030 2031 2032 2033 2034 2035
Table 2.1: Biennial Conservation Target for Washington Energy Efficiency
2026-2027 Biennial Target (MWh)
CPA Pro-Rats Share 73,672
NEEA Programs 12,877
EIA Target 86,549
Decoupling Threshold 4,327
Total Utility Conservation Goal 90,877
Excluded Programs NEEA -12,877
Utility Specific Conservation Goal 77,999
Decoupling Threshold -4,327
EIA Penalty Threshold 73,672
Demand Response Selections
Demand response (DR), Virtual Power Plants (VPPs), and/or modified retail pricing
programs will be integral to Avista's strategy to meet peak customer load requirements
with non-emitting resources. Avista added 30 MW of industrial DR within the last three
years and agreed to pilot three DR programs in the 2021 CEIP process. There is
uncertainty in these programs' ability to meet planning reserve margin (PRM) due to the
time duration limits and load snap back effects without traditional resources available to
meet high demand days. Further, programs using retail rates, such as Time of Use (TOU)
rates, are not dispatchable and are dependent on customers' willingness to participate at
the time of a DR event. Given these concerns, DR's valuation within the IRP may change
Avista Corp 2025 Electric IRP 53

Chapter 2: Preferred Resource Strategy
in the future based on learnings derived from the pilot efforts. Chapter 6 has more details
about DR options considered in this plan.
Three major changes from the 2023 IRP when evaluating DR include:
(1) Use of a capacity adjustment by assuming the demand reduction lowers load and
therefore lowers the total MWs estimated in the planning reserve margin (PRM).
(2) Programs assume a Transmission & Distribution (T&D) financial credit of $25.38
per kW-year' to account for potential savings in T&D investment.
(3) The Qualifying Capacity Credit (QCC) do not degrade over time as compared to
the 2023 IRP.$
These changes significantly increase future DR programs compared to prior IRPs, and,
along with updated costs and program assumptions, lead to the savings shown in Figure
2.4. DR selections total 51.6 MW of winter savings in Washington by 2045 (56.3 MW
summer) and 10.6 MW winter (4.3 MW summer) in Idaho. The programs by year and
state are shown in Table 2.2. Without advanced metering infrastructure in Idaho until
2029, Idaho DR programs are deployed later than Washington due to later automated
meter infrastructure deployment. Overall, less DR is expected in Idaho due to lower-cost
alternatives such as natural gas turbines, whereas Washington must use higher-cost
methods to meet peaks due to CETA requirements. When combining existing DR
programs with the PRS's DR selection, system peak load could be reduced 4% by 2045,
with Washington programs decreasing peak load between 5% and 6%.
Avista is piloting TOU rates and Peak Time Rebate programs over the next two years
(2025-2026)and partnering with Northwest Energy Efficiency Alliance (NEEA)to evaluate
CTA-2045 grid-enabled water heaters (see Chapter 6 for further information). Lessons
learned from these pilots will provide greater understanding of the program benefits,
costs, and acceptance to determine whether DR will be selected earlier in the 2027 IRP
as compared to this plan's selection. If the capacity need is greater, DR in Washington
would likely be selected earlier. However, due to other resources being selected to meet
the capacity need, DR is pushed to periods when greater resource deficits occur. Avista
expects third-party aggregators will submit proposals in future RFPs where the DR
resource could be more cost effective compared to other options.
The credit was created by the revenue requirement of net value of current T&D plant assets on a historic
basis and is compared against the peak load for the system to estimate a $/kW-year value.
8 The 2023 IRP assumed the QCC value by 2045 is 20% of the 2024 value. This IRP assumes the 2045
value is 80% of the 2026 QCC value, significantly increasing the amount of capacity DR is assumed to
deliver to the system.
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Chapter 2: Preferred Resource Strategy
Figure 2.4: Total Demand Response by State and Year in Winter
70
■Winter WA +Winter ID
60
50
rn
40
m 30
20
10
(O � (r) (O r. M O (D N M � U)
N N N N M M M M M M M M M M N Nt `t `t Nt
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Table 2.2: Demand Response Selection
Electric Vehicle TOU Commercial Available 2029
Battery Energy Storage All 2026 2035
Variable Peak Pricing Large Com./Ind. 2026 2029
Peak Time Rebate Res./Com. 2035 2040
Behavioral Res./Com. 2038 2043
Time of Use Rates Res./Com. 2038 n/a
Third Party Contracts Large Com. 2039 2044
CTA ERWH Res./Com. 2041 n/a
Central A/C Res./Com. 2043 n/a
Washington Named Community Investment Fund (NCIF)
The IRP focuses on ensuring enough energy or capacity is available to meet customer
load for specific periods of time. The NCIF will fund future projects with unknown energy
benefits and will be developed based on direction from the communities Avista serves.
Even though the specific actions or projects are unknown, the IRP needs to account for
these benefits by reducing resource acquisition targets. The actual funding decisions may
or may not impact overall resource needs and rely on Avista's Equity Advisory Group's
(EAG) recommendations. Given an IRP cannot forecast specific projects, this analysis is
designed to estimate possible project impacts by selecting resources or energy efficiency
programs meeting NCIF objectives. This is done by including $0.4 million of incremental
supply-side DERs each year (after tax incentives) and providing an additional $2 million
of energy efficiency upfront spending estimated by the present value of the Utility Cost
Test (UCT) for resource selection.
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Chapter 2: Preferred Resource Strategy
The result of this effort is the selection of approximately 22.1 MW of community solar
through 2045. The quantity of community solar is a direct result of Washington State
(Commerce) and NCIF funding covering 100% of the community solar costs including
administration. The IRP modeling suggests between 2026 and 2033, the period when
Commerce funding is available, 9.9 MW (AC) could be developed (1.4 MW per year).
After the state funding expires, the new solar estimate drops to 1 MW per year. The total
final amount of solar added to benefit these communities may differ from this forecast and
will be determined based on upon available funding and project limitations. Due to project
funding priorities, it is also possible that no community solar is added if the funds are
allocated to other projects.
In addition to assumed new community solar, Avista's energy efficiency targets are 3.4%,
or 22.4 GWh higher to reflect additional investments in Named Communities through
2045.9 For the 2026-27 biennial period, the energy efficiency target increases 3% to
reflect this anticipated additional spending. Each of these activities along with the energy
efficiency for low-income households outside of the NCIP contribute toward meeting the
energy assistance needs of our communities with distributed energy resources as
required by 480-100-620(3)(b)(iii).
Distribution Scale Energy Storage
Using energy storage on the distribution system may mitigate the need for upgrading
certain portions of the delivery system when summer peak temperatures drive the need
for enhancing distribution substations. This IRP did not identify any distribution level
storage using generic system benefits combined with energy benefits. This does not
mean future projects lack economic value or will not be the least cost solution for
customers, but rather when analyzing future distribution system needs, the study will need
to be performed using this IRP's avoided cost calculations to evaluate potential feeder
upgrades against traditional methods of delivering energy. The 2027 IRP will incorporate
any known potential for feeders where the distribution plan determines if energy storage
is a solution to solve future needs of the delivery system.
Supply-Side Resource Selections
The PRS is designed to meet resource needs described in Chapter 5 with generic new
resources as described in the DER (Chapter 6) and supply-side resources (Chapter 7)
chapters. When Avista prepares to acquire new resources for its energy/capacity needs,
an All-Source RFP will be issued to find the best resource options to meet the need rather
than using specific IRP resource requirements. The resource strategy discussed here is
based on the best available information for planning purposes and is a result of future
load expectations and resource pricing. Due to uncertainty about these planning
9 For energy efficiency, energy potential is estimated using low-income versus non-low income and does
not include geographic areas.
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Chapter 2: Preferred Resource Strategy
assumptions, Avista continuously evaluates the alternative portfolios discussed in
Chapter 10 and will continue to revise this plan every two years.
Avista separates resource selection between its two jurisdictions in this plan due to
differing state-level policy objectives and financial evaluation methodologies. Each state
is separated according to its load along with its planning risk adjustments (totaling the
planning obligation). Existing resources are netted against the obligation for each state
using the existing Production Transmission (PT) ratio to allocate resource costs,
approximately 65.5% assigned to Washington and 34.5% to Idaho in 2026. The PT ratio
is adjusted each year based on the expected state-level load changes within the load
forecast. The amount of assigned existing resources shifts to the faster-growing state as
it gets a higher percentage of the PT ratio. In addition the splitting resources by the PT
ratio, PURPA resources are assigned to the jurisdiction of qualification. New resources
are then selected based on the objective function described later in this chapter to fill any
needs.
-xistinq Thermal Generation Forecast
The resource strategy includes the retirement or exit of several resources from the
existing power supply portfolio. The first resource exit is the 222 MW of Colstrip Units 3
and 4 at the end of 2025 when ownership is transferred to NorthWestern Energy. There
are also approximate retirement dates and PPA expirations for several of Avista's natural
gas peaking and wind facilities. While these dates are subject to change, this plan uses
current expected retirement dates to determine the need for additional resources. These
retirements include Northeast by the end of 2029, Kettle Falls combustion turbine (CT)
and Boulder Park CT by the end of 2039, and Rathdrum CT by the end of 2044. The
Lancaster PPA concludes at the end of 2041, and Coyote Springs 2, the final natural gas
facility, does not have a planned retirement year. Given CETA's 2045 100% clean energy
requirement, this IRP determines Coyote Springs 2 in 2045 could co-firing 30% of its fuel
with hydrogen for Washington customers and allocate the remaining 70% of the
production to Idaho customers. Table 2.3 summarizes resource retirement assumptions.
Avista's schedule for long-term power purchase contracts, including wind PPAs, are
included in Chapter 4. Currently, Avista has no plans to retire any of its hydroelectric
resources.
Table 2.3: Thermal Resource Portfolio Exit Assume.,..,
CapacityResource FuelType Final
Northeast Natural Gas 2029 64.0
Boulder Park Natural Gas 2039 24.6
Kettle Falls CT Natural Gas 2039 10.9
Lancaster Natural Gas 2041 281.7
Rathdrum CTs Natural Gas 2044 174.5
Total 555.7
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Chapter 2: Preferred Resource Strategy
Supply-Side Resource Selections (2026 to 2035)
Avista recently completed a large resource acquisition process acquiring long-term
contracts for hydroelectric power from Chelan PUD and Columbia Basin Hydro, extending
the Lancaster PPA, and adding the Clearwater Wind PPA. Following the 2023 IRP, Avista
expected these acquisitions would create a long position and new resources would not
be required for a few years. However, the long resource position quickly dissipated with
the addition of a large-load customer and overall customer load growth, especially in
winter peaks. These changes now show a small energy and capacity deficit in January
2026, while most of the remaining months are long until 2030.
Avista plans to meet small capacity and energy deficits between 2026 and 2029 by using
short term market purchases and the demand response programs mentioned earlier in
this chapter. To meet the Idaho customer portion of the 2030 capacity deficit, a 90 MW
natural gas combustion turbine (CT) is selected. This resource replaces the expected lost
capacity of the Northeast CT and addresses future natural gas retirements while
accommodating load growth in Idaho. This analysis models this capacity addition as a
third unit at the Rathdrum CT site. Table 2.4 summarizes the capacity addition plan
through 2035. Avista expects the RFP resource selection will be different from this IRP,
as the IRP assumes non-specific project sites, interconnection, and locational budgets in
its evaluation whereas the proposals received in the RFP will have specific projects and
costs.
The 2023 IRP determined that the early acquisition of 400 MW of wind was cost-effective
due to available production tax credits. This plan produces the same result but also shows
the need for additional wind capacity due to the higher electric market price forecast and
the potential for more wind availability than assumed in the prior plan. This plan selects
200 MW of northwest wind in 2029, followed by an additional 200 MW each year through
2032 and 157 MW in 2033 for a total of 857 MW of wind. This includes wind located in
Montana and off Avista's transmission system but still within the northwest. This IRP finds
customers benefit in both states by selecting 357 MW of wind as a system resource and
500 MW as a Washington-only resource. However, this selection of wind comes with
several important caveats:
• These selections are a result of high electric market prices and low-
priced wind PPAs. If actual PPA pricing is higher or market prices fall,
the resource selection will change as a result of the RFP process.
• Avista's transmission system can accommodate up to 500 MW10 of
wind without substantial transmission expansion. If wind projects are
exported off Avista's system, the resource selection will result in less
wind for Avista customers at low pricing.
10 The 2023 IRP assumed only 200 MW of additional wind would be available without major transmission
expansion.
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Chapter 2: Preferred Resource Strategy
• The model assumes tax credits will expire in 20321' and not be
extended, thus driving early acquisition. If tax credits expire early, or
are extended, the wind acquisition strategy will change.
To account for this uncertainty, the plan will be revised in the 2027 IRP. However, a future
all-source RFP will provide real options to evaluate whether early acquisition of this
amount of wind is cost effective given Avista's resource needs.
fable 2.4: Resource Selections (2026-2035)
CapabilityResource Year -]-Jurisdiction Capability Energy
Northwest Wind 2029 Washington 200 69
Northwest Wind 2030 Washington 200 69
Natural Gas CT 2030 Idaho 90 86
Northwest Wind 2031 Washington 100 34
Montana Wind 2031 System 100 44
Montana Wind 2032 System 100 44
Northwest Wind 2033 System 157 54
Total 947 399
Supply-Side Resource Selections (2036 to 2045)
The IRP did not select utility-scale supply-side resources between 2034 and 2040 due to
the early acquisition of renewables, the utilization of new transmission, and the ability of
DR and energy efficiency to meet load growth-related requirements. As Washington's
100% clean energy target approaches, the deadline to replace natural gas resources,
while meeting higher load growth due to electrification, will require substantial new
resources after 2040. Idaho resource needs follow load growth and natural gas resource
retirements. Table 2.5 outlines the resource additions and the associated production from
added resources between 2036 and 2045. New resources are selected using familiar
technologies such as natural gas turbines, wind, solar, lithium-ion batteries, and biomass,
but also technologies new to Avista, including power-to-gas combustion turbines (CTs),
nuclear, iron-oxide energy storage, and geothermal. While 2045 is a long way off, Avista
will need to follow technology development and potentially develop sites for these
resources up to 10 years ahead of need. Therefore, the 2045 targets will be continually
evaluated in future RFPs to ensure resources can be developed in time to meet state
goals.
To meet Washington's 2045 clean energy requirements, a diversified mix of new
resources will be required including wind, solar, 4-hour lithium-ion energy storage,
biomass, geothermal, nuclear, and 100-hour iron-oxide energy storage. Power-to-gas
technologies, where renewable energy is converted to hydrogen and either consumed
directly as hydrogen or converted into ammonia, are also required. As mentioned earlier,
11 The credit may be extended for projects meeting the safe harbor construction requirements.
Avista Corp 2025 Electric IRP 59

Chapter 2: Preferred Resource Strategy
the 2036-2045 strategy also includes co-firing a 30% hydrogen blend in the Coyote
Springs 2 facility to enable the plant to continue to provide some capacity to Washington
customers.
With the addition of natural gas resources to meet Idaho needs, adequate fuel supply is
needed, but existing regional pipelines are contractually full. To address this concern in
the plan, Avista includes the proportionate cost of a new LNG storage facility within the
cost of new natural gas generation. If firm fuel supply is not ultimately available, Avista
may need to pursue natural gas storage in the local vicinity of the generation to ensure
the ability to generate in winter peak events.
Table 2.5: PRS Resource Selections (2036-2045)
Resource Year Jurisdiction Capacity Energy
(MW) Capability
Natural Gas CT 2040 Idaho 90 86
Power to Gas CT 2040 Washington 90 5
PPA Wind Renewal/Repower 2041 Washington 140 48
Natural Gas CT 2042 Idaho 95 90
Power to Gas CT 2042 Washington 210 11
PPA Wind Renewal/Re ower 2043 Washington 120 41
Solar+ 90 MW 4-hour Storage 2043 Washington 180/90 53
Solar+ 60 MW 4-hour Storage 2044 Washington 120/60 36
Iron-Oxide 100-hour Storage 2044 Washington 26 n/a
Northwest Wind 2044 Washington 108 37
Iron-Oxide 100-hour Storage 2045 Washington 85 n/a
Nuclear 2045 Washington 100 98
Northwest Wind 2045 Washington 200 69
Geothermal 2045 Washington 20 18
Kettle Falls Upgrade 2045 System 10 9
Kettle Falls Unit 2 2045 Washington 58 29
Coyote Springs 2 Hydrogen Co-Fire 2045 Washington n/a n/a
Total 1,652 629
Transmission Requirements
Avista will require new transmission to integrate new generating resources and access
new markets. Historically, the IRP only modeled interconnection costs for new resources
and did not conduct detailed transmission studies. Avista does, however, develop a 10-
year transmission plan with specific transmission projects (see Appendix D). The IRP
considers limits on resources with low-cost interconnections and determines whether
resource need triggers a major transmission build. As a result of this analysis, the IRP
modeling identified upgrades to integrate new generation in the Rathdrum, Idaho area.
This location will likely be the site of future generation, whether it be natural gas,
hydrogen-based fuels, or energy storage. Increasing the intertie between north Idaho and
Spokane is required to site any generation.
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The second major project is a new DC transmission line between Colstrip, Montana, and
North Dakota. This proposed line by Grid United would create a diversified market for
Avista to participate in for energy purchases and sales. This market could provide reliable
capacity to offset the need for building new generation resources due to diversity in time,
weather, and other market conditions. Furthermore, this line could allow Avista and other
utilities to arbitrage the price differences between the Northwest and the Midcontinent
Independent System Operator (MISO) and/or Southwest Power Pool (SPP) markets to
benefit customers.
In this IRP, Avista modeled this transmission resource as providing a capacity benefit in
a limited manner when Montana wind generation is not available. The initial analysis did
not consider any arbitrage value as this analysis will be evaluated outside of the IRP prior
to making any investment decision. With these assumptions, the new line was selected
by the model in 50 MW increments for the Washington service area. Avista then evaluated
whether the arbitrage value would select the new transmission line earlier, all at once, or
for both jurisdictions. Avista found adding a minimal arbitrage value results in the model
selecting the line all at once for both jurisdictions. Therefore, this IRP assumes Avista will
participate in the line at 300 MW with an expected on-line date of 2033. At the time of this
IRP, Avista signed a Memorandum of Understanding to continue exploring this option
with Grid United. Initial IRP analysis shows the new transmission line appears to be a
favorable project in lieu of alternative generation resources and Avista will continue to
evaluate the economics of this project between this IRP and the 2027 IRP.12
Avista has limited firm transmission rights to the Mid-Columbia market and other regions.
This IRP identifies that Avista should invest in new transmission projects to increase
connectivity to both markets and/or other balancing authorities to import resources and
diversify market access. The challenge with this conclusion is identifying the specific
locations and markets for these transmission enhancements when the location of new
resources is uncertain.
The last new transmission asset Avista should consider developing is the Big Bend area
in the western part of its system. This area has solar and wind potential but needs new
transmission to deliver these resources to Avista's load or to other utilities. This IRP did
not specifically select resources in this area due to the approximate $260 million cost and
10 or more years of development time to expand the system. Given the risk of wind
resources in low-cost connection areas of the transmission system being exported to
another buyer, Avista may need to access wind resources for the 2045 100% clean
energy compliance. Developing this transmission may give Avista optionality to meet
future load needs if lower cost wind is not available when needed or loads grow faster
than anticipated.
12 The IRP analysis was conducted prior to the announcement by the DOE awarding a $605 million Grid
Resilience and Innovation Partnership (GRIP) grant to the project.
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Power-to-Gas Fuels
Toward the end of this plan, Avista identifies two types of power-to-gas (P2G) projects.
The first is to co-fire hydrogen at Coyote Springs 213 for up to 30% of its fuel supply by
2045. To achieve this, additional hardware will be required at the facility along with new
fuel-handling equipment. This includes a dual gas control module, manifold skid,
hazardous gas and fire detection system upgrades, detection systems, adding welded
fuel nozzles, metering and sensors, and an additional selective catalytic reduction (SCR)
catalyst or ammonia injection component to reduce NOx emissions. However, the biggest
challenge will be sourcing the hydrogen fuel supply. The IRP analysis assumes a fuel
delivery system will be in place, although the method of fuel delivery and/or storage is
unknown. The Pacific Northwest Hydrogen Hub, funded in part by the U.S. Department
of Energy, or separate hydrogen supply chain with on-site fuel storage are potential
options.
The second P2G project identified in this plan is new combustion turbines using clean
energy-based ammonia. Ammonia can be commercially derived from hydrogen produced
by excess clean energy and efficiently stored and transported. Turbine manufacturers are
developing turbines capable of using this fuel source. This IRP assumes ammonia is a
cost-effective way to store energy in a relatively small footprint for long durations. This
technology does not use natural gas as fuel but operates with similar characteristics. The
advantage with ammonia, compared to hydrogen, is the ability to store large quantities
without underground storage, and the ability to transport the energy via rail or truck.
Significant infrastructure for ammonia production, handling and storage for industrial and
agricultural use already exists. Due to hydrogen and ammonia being new generation fuels
with no major supply chain in place in the Northwest for this use, Avista limited this
technology to 300 MW. Absent a robust supply chain similar to the natural gas system,
Avista would need four 30,000 metric ton tanks to store the fuel to meet the high fuel
usage scenario studied in this plan. Due to storage requirements and safety concerns,
Avista limits the locations for this technology to larger land requirements than a similar
natural gas facility with access to pipelines.
The storage needs of these ammonia facilities will be determined by how much the facility
is expected to operate and what energy is used to create the fuel. For example, if solar
and water were to be used in the development of the ammonia through hydrolysis and
the Haber-Bosch process in the 95t" percentile use case (i.e., ammonia is called on to run
at a 19% capacity factor), it would require an equivalent 1,600 MW of solar capacity using
a 13.4% round trip efficiency rate from solar power to long-duration dispatchable
ammonia power. However, if the ammonia creation were not dependent on solar energy
and refilled faster during winter months, the storage requirements to operate at higher
capacity factors would be less due to a just-in-time delivery system. Given ammonia is a
world-wide commodity, it is possible Avista will be able to access supply without having
13 GE has expressed this technology's maximum hydrogen co-fire ability is 32%, so 30% is used as a
conservative planning estimate.
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Chapter 2: Preferred Resource Strategy
to internally develop its own supply chain, reducing the need for large amounts of storage
and self-development of additional renewable resources dedicated to fuel production.
Given this identified technology need is more than 10 years away, Avista can monitor the
development of both the generation technology and supply chain for this option. If
ammonia for power generation does mature at the generation or fuel level.
An alternative fuel is synthetic methane. The fuel is expected to be higher priced but uses
the same principle of clean hydrogen but uses carbon dioxide rather than nitrogen for
chemical bonding. An advantage of this fuel is it can use existing generation technology
and fuel delivery systems, but the technology is still in its infancy.
Nuclear Energy
For the first time since the 1980s, nuclear power appears in the resource plan. While not
appearing until 2045, small modular reactors (SMR) could play a key role in developing
a reliable and clean resource portfolio replacing Avista's natural gas resources. Given the
time horizon for the selection, Avista will continue to monitor this resource development
as other utilities and developers are pursuing it. Avista will need to consider all resource
options to meet the clean capacity acquisitions needed beginning in 2040. With potential
long lead time and permitting, the development and procurement phase of this resource
may need to begin as early as 2030 to ensure it can be completed in time.
System Overview
Figures 2.5 through 2.7 summarize the future resource additions by combining the
existing portfolio of resources, with already-contracted additions and future resource
selections from this plan. The black solid line represents the planning load resources
expected to meet (including expected load and a planning margin or reserves to account
for unexpected conditions) and the dotted line represents expected load given normal
conditions.
Historically, Avista operated in a long-capacity resource position — meaning resource
capability exceeds expected load. But as shown in Figure 2.5, the resource portfolio is
nearly balanced until 2033 with the forecasted completion of the North Plains intertie with
MISO/SPP. While the planning margin target is met, the risk of meeting customer load is
still a concern in the event of unplanned extreme weather conditions or the inability to buy
power from the energy market. For example, during the January 2024 cold snap, Avista
was near a resource-even position, but extreme cold temperatures and low hydroelectric
conditions combined with a temporary loss of generation assets due to natural gas
delivery system constraints required Avista to depend on the energy market.
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Chapter 2: Preferred Resource Strategy
Figure 2.5: System Winter Capacity Load & Resources
3,500
3,000
2,500
_ado
2,000
3
R
1,500
1,000
�Owned&Contracted Hydro Wind/Solar/Biomass/PURPA New Solar/Wind
500 �Existing Natural Gas New Natural Gas New Clean Dispatchable Fuels
�New Energy Storage New MISO/SPP Market Intertie —Planning Load
——Expected Load
(O � 00 O O N (M 7 O (0 r` aD 0) O N M V u)
N N N N M M M M M M M M M M V V V V V V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
The summer capacity position in Figure 2.6 is similar to the winter position, except the
portfolio has slightly more excess capacity because the winter capacity targets are the
more difficult constraint to meet. Avista plans for a smaller planning margin in the summer
compared to winter due to several factors. The system is less reliant on hydroelectric
energy as the peak summer hour duration is shorter than winter. Another factor is summer
peak loads do not vary year to year as much as winter peaks due to less peak day
temperature variation.
Figure 2.6: System Summer Capacity Load & Resources
3,500
3,000
2,500
a2,000
3
m
rn
4)1,500
1,000
Owned&Contracted Hydro Wind/Solar/Biomass/PURPA �New Solar/Wind
500 Existing Natural Gas New Natural Gas �New Clean Dispatchable Fuels
New Energy Storage New MISO/SPP Market Intertie -Planning Load
Expected Load
(0 1­ CO 0) O N CO V O (O 1- 00 0) O N CO 7 LO
N N N N co M M M M M M M M M V 7 V V 7 V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Avista's annual energy position (Figure 2.7) is long compared to the annual average
needs because:
(1) Avista solves to meet monthly energy requirements, Avista is generally more
constrained in winter and summer months and acquiring energy to meet these
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Chapter 2: Preferred Resource Strategy
shortages creates length in other months since you typically cannot develop or
obtain contracts for resources with operations limited to one period of time.
(2) Excess energy in the spring from hydroelectric and wind generation creates an
extremely long position compared with load than other seasons.
(3) Avista plans its system to meet peak load requirements. The generation can create
excess energy in other time periods when not needed for Avista customers and
can be sold to benefit customers assuming the resource is economic to operate.
The solid black line in Figure 2.7 represents the planning load level including the risk of
load exceeding expected average weather conditions and/or renewable energy volatility,
such as hydroelectric or wind, producing less generation than anticipated in a normal
year. The dotted line is the expected average load under normal weather conditions.
Figure 2.7: System Annual Energy Load & Resources
3,500
�Owned&Contracted Hydro —Wind/Solar/Biomass/PURPA �New Solar/Wind
�Existing Natural Gas New Natural Gas —New Clean Dispatchable Fuels
3,000 —New Energy Storage �New MISO/SPP Market Intertie —Planning Load
—Expected Load
2,500
3
a, 2,000
d
m
1,500
`m
1,000
500
0
(O h co O O N M V LO O n 00 M O N M V in
N N N N M M M co M M M M co M V V V - V V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Resource Adequacy Analysis
One of the greatest modeling challenges for the IRP is developing a capacity expansion
model to optimize resource selections to meet resource adequacy requirements in a
lowest cost manner. The current industry standard for testing resource adequacy is to
conduct Monte-Carlo or stochastic analysis of hourly operations to evaluate the
probability of not meeting loads with any given resource portfolio. With today's
technology, and the large number of simulations over multiple forecast years, it is not
possible to add a capacity expansion optimization routine to this effort. To overcome this
challenge, capacity expansion models such as PRISM use a target for adding resources,
such as expected load plus a planning margin and develop a system to quantify how
resources can meet these load targets, known as Qualifying Capacity Credits (QCC).
Avista assigns QCCs to each resource for each forward month to ensure the model
selects enough capacity to meet the load target. To validate whether this resource
selection passes a Monte Carlo style resource adequacy evaluation, a resource
adequacy analysis is required after the PRS is determined.
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Chapter 2: Preferred Resource Strategy
Avista developed an hourly tool called Avista Resource Adequacy Model (ARAM) to
assess resource portfolios for resource adequacy — see Chapter 5 for more information
on this model and reliability metrics. This IRP tests two future years (2030 and 2045)
using this tool to ensure the PRS complies with Avista resource adequacy tests. Avista's
primary focus for reliability planning is to meet a 5% loss of load probability (LOLP). This
target means Avista would meet all load requirements in 95% of all future conditions while
not exceeding 330 MW of market purchases during capacity-constrained hours. For the
2030 and 2045 periods when adding future resources, the PRS meets this requirement
with a 3.2% probability in 2030 and 3.3% probability in 2045 as shown in Table 2.6. The
reason the LOLP is below the 5% threshold is the capacity expansion model suggests a
higher resource buildout than required, whereas the minimum PRM is 24%, but in 2030
and 2045 the resource PRM is 29.6% and 28.6% respectively. This resource length
pushes down the resulting LOLP. Also shown are other industry standard reliability
metrics used to evaluate resource adequacy. Although the PRS results in a LOLP less
than 5%, this does not guarantee Avista will be able to meet 100% of its load in all
conditions. For example, in a high load and low water event, the utility still may have to
rely on the market above the assumed 330 MW market limits (plus 300 MW for 2045
when the eastern interconnect transmission is considered) or risk failing to serve all load.
Table 2.6: Reliability Metrics
Metric 2030 w/o 2030 w/ LU143 W
new PRS
resources
LOLP 6.9% 3.2% 3.3%
LOLE 0.227 0.07 0.09
LOLH 2.59 0.73 1.1
LOLEV 0.495 0.176 0.304
EUE 488 115 172
Washington Hourly Clean Energy Analysis
The "use" rules for compliance with CETA's clean energy standard are still being
developed by the Washington UTC. The Washington Department of Commerce
(governing consumer owned utilities) rules include an hourly analysis requirement in
planning. Avista assumes the UTC rules will include a similar requirement for the
development of this plan. Today's capacity expansion models (such as PRiSM) are not
able to model at an hourly level of granularity when selecting new resources over 20
years. This limitation also exists in commercially available software, and while
theoretically possible, the solution time is likely too long to be useful. In Avista's situation,
PRiSM solves the system monthly using hourly data from the Aurora model.
For this first hourly analysis, the hourly data from the Aurora modeling is analyzed to
determine how well the energy matches up to (retail) load on an hourly basis using
market-based dispatch of resources. However, this methodology does not show how the
utility could use its resources to meet only its load, but rather it dispatches resources to
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Chapter 2: Preferred Resource Strategy
serve regional load (market) as to reflect actual future operations. This is because utilities
do not dispatch resources to serve only their own load, but also regional demand based
on market prices, allowing the utility to optimize its resource portfolio for the benefit of its
customers by selling excess energy to others when prices are high and purchasing from
the market when prices are lower. Avista is conducting a second analysis to determine
whether it could meet the hourly 100% clean energy goal in 2045 if the utility were to
dispatch its resources only to load without the market (discussed below).
For this first view of hourly compliance using market-based dispatch, Figure 2.8 provides
an annual summary of the results, where the black line represents the annual goal of
"primary" compliance or the total amount of energy as a percentage of retail load where
clean energy must be generated in the same hour. In 2045, the clean energy goal is
slightly above retail load due to the fact Avista must serve all Washington retail load and
line losses with clean energy. The orange lines represent how well the Avista portfolio
performs against this requirement. The solid orange line includes both the allocated clean
energy to Washington based on the current PT ratio plus the transferrable portion from
Idaho. As a reference, the dashed orange line shows only the Washington allocated
portion. Avista meets the hourly requirement in all years until 2042. In 2042, 94% of the
load in all hours is met with clean energy compared to the goal of 95% (assuming market-
based dispatch).
The solid blue line represents how much additional clean energy is produced, but the
energy produced is excess to the hourly load when the model dispatches to regional
loads. The next step is to determine if the Company "could" serve the load targets
between 2042 and 2045 by either moving clean energy generation to different hours using
either future energy storage or existing hydroelectric storage, or increased amounts of
dispatchable clean energy such as ammonia turbines to achieve these targets. This
analysis will be performed for only the 2045 period in the final IRP, assuming 2045 could
be solved with Avista flexible resources, meeting 2042-2044 could be assumed to be
capable as well.
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Chapter 2: Preferred Resource Strategy
Figure 2.8: CETA Hourly Analysis
120%
100%
i
i
i
80% I�
p --- —♦
J —Primary Clean Energy Target
� ——— Allocated Share%
60%
Allocated+ ID Transferable%
Excess Gen vs Load%
C 40%
d
v
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a
20%
0% _ _
CO I- 00 O) O N M It LD O r- 00 O O N M I. LO
N N N N M M M M M CO M M M M V V V V V V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
2045 100% Clean Energy Analysis
Avista's hourly modeling approach, as described in the previous section, dispatches
resources to market. Avista anticipates market purchases will continue to be a method of
meeting load in the future but may require a clean energy market to ensure compliance
with CETA. However, Avista tested if Avista's 2045 portfolio could in fact serve 100% of
its Washington load with clean energy if it were to redispatch resources to meet load
demands. The concept requires resources with energy storage (batteries and hydro) and
fuel (ammonia) to redispatch to generation to meet load each hour. Resources such as
hydrogen, ammonia, and biomass are limited in annual dispatch to ensure fuel availability.
For example, Kettle Falls Unit 2 is limited to 50% capacity factor due to limited wood fuel.
The model then solves using the same monthly hydro levels and hourly wind and solar
generation from Figure 2.6. Effectively, the model solves dispatchable resources to meet
load. Figure 2.7 shows the results of this analysis by month. The results show Avista can
meet 100% of Washington load with clean energy when average load and renewable
generation is assumed; in fact, it has excess generation in many of the hours. The model
also did not require any of the Idaho share of clean resources in this example. Although,
in non-spring months, the model found many hours where clean generation equals load
exactly. For example, in January 2045, 41% of the hour's clean generation equals load,
but overall, in the month, 14% more clean generation was created versus actual load.
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Chapter 2: Preferred Resource Strategy
Table 2.7: 2045 Hourly Aiidiybib
Month Clean Percent of
Energy % Hours Clean
Generation
. . .
1 114% 41%
2 123% 4%
3 137% 0%
4 165% 0%
5 178% 0%
6 170% 0%
7 134% 3%
8 120% 31%
9 132% 15%
10 126% 32%
11 114% 39%
12 121% 35%
Emissions Forecast
Avista's recent resource portfolio changes will significantly improve its air emission profile.
These portfolio changes include transferring ownership of Colstrip Units 3 and 4 to
NorthWestern Energy at the end of 2025 and replacing this generation by signing
hydroelectric power purchase agreements (PPAs) with Chelan PUD and Columbia Basin
Hydro, as well as a 100 MW PPA from Clearwater Wind. Figure 2.8 illustrates the
expected clean energy generation as a percentage of customer load by year and by
jurisdiction. The chart compares total annual clean energy production for each state's
allocated share of energy14 compared to its estimated state load. In Washington, Avista
will need to produce more clean energy than its load to meet the hourly 100% clean
energy requirements. On a system basis, the resource portfolio by 2045 could generate
10% excess clean energy as compared to annual average load.
This over generation phenomenon is due to CETA requiring Washington's load to meet
100% of its generation needs using renewable or non-emitting generation in all hours and
under all-weather scenarios. This includes meeting higher needs in summer or winter
months with clean energy and accounting for renewable and load variability when there
are low hydroelectric or wind years. This requirement will create substantial amounts of
surplus generation in months with lower loads. This high level of surplus power will be
compounded by all other Washington utilities also having surplus production beyond their
needs, driving market prices to very low or negative levels. This oversupply could spur
development of hydrogen to assist fueling future hydrogen/ammonia CTs. When Avista
evaluates meeting CETA's 100% clean energy requirements, three resource strategies
could take place in the future:
14 This excludes potential transfers of clean energy between states to satisfy CETA requirements.
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Chapter 2: Preferred Resource Strategy
(1) building long duration energy storage to move renewable energy from lower to
higher load periods,
(2) having enough variable energy resources (VER) in place to statistically be able to
generate at least the amount of energy needed in higher load periods, or
(3) controlling or owning dispatchable clean generation such as nuclear or biomass.
The 2023 IRP results solve the 2045 challenge, this IRP includes more renewable/non-
emitting generation and less energy storage by 2045. The 2025 PRS assumes a more
diversified mix of resources including components of all three options to achieve the 100%
goal. However, the maturity of some of these technologies, such as long-term storage or
nuclear, may not be at a level of commercial availability for a decade or more. Clean
resource choices will ultimately be based on the economics of each of the options
compared to the cost increase caps set by CETA.
While Avista's resource plan includes significant renewable energy additions, greenhouse
gas emissions will still not be zero. Figure 2.9 compares greenhouse gas emissions from
2023 (red line) and the 2019-2023 average (black line) from Avista controlled generation
to the forecasted emissions from this plan. When looking at Avista controlled generation's
2026 forecast of emissions (blue bar), emissions are expected to be 59% less than 2023's
or 49% less than the 5-year average.
This reduction is mainly due to the removal of Colstrip from the resource portfolio. Also,
emissions were higher in 2023 due to a lower-than-normal water year in the Northwest,
thus driving market prices higher and making both coal and natural gas cost effective to
run at higher capacity factors. Avista expects 2024 may also show higher greenhouse
gas emissions due to even lower water availability for hydroelectric generation in the
region.
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Chapter 2: Preferred Resource Strategy
Figure 2.9: System and State Clean Energy Ratios Compared to Load
140%
120% ■Currently Controlled Resources
■Resource Selections
100%
�
0 28% 77%
° 13% 12% 35% 27% 55%
-a 80% 11%
J 10%
4- 60%
O
C
d 40% o
L 75/0 72% 73% 71% 66% 68%
d 60% 56%
d 20%
0%
0 C E 0 C E 0 C E 0 C E 0 C E
m 0 N O a) O 0 O CD0 N
L (n t (n L CO L U) L (n
>N >N >N >N >N
2026 2030 2035 2040 2045
Figure 2.9 also includes estimates for upstream emissions related to natural gas
deliveries, construction of new facilities, and plant operations. The chart also estimates
the effect of market transaction emissions on the portfolio by either subtracting or adding
emissions based on Avista's position — whether Avista is a net buyer or seller of energy
(green bar). Emissions notably decline in 2031 due to assuming regional generators will
not be given free allowances in the same manner as today under Washington's Climate
Commitment Act (CCA), effectively requiring a greater number of facilities to account for
the price of carbon when dispatching generating plants. The major drop in current
resource emissions in 2042 is due to the expiration of the Lancaster PPA. This plan
assumes it is replaced by additional natural gas CTs as shown in the orange bars
operating at lower capacity factors. Even with the addition of new natural gas CTs
replacing existing facilities, 2045 emissions are estimated to be 82% lower than the 5-
year average from 2019 through 2023.
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Chapter 2: Preferred Resource Strategy
Figure 2.10: Avista System Greenhouse Gas Emissions
4.5
4.0
3.5
3.0
y
O
2.5
Current Resources New Resources
2.0 Net Market Transactions —Upstream/Construction/Operations
y —Net Emissions —2023 Generated Emissions
1.5 —5-Yr Avg.Generated Emissions
O
1.0
0.5
0.0
-0.5
-1.0
(0 I— 00 0) O N M 7 LO Co 1­ 00 M O N co V Lo
N N N N co M M Cl) Cl) co co co M Cl) V V V V 7 7
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
An alternative method to calculate total greenhouse gas emissions is to calculate the
emission intensity of load. In this example, the total plant emissions (where Avista controls
dispatch) are divided by the system load on a pounds per MWh basis. In this case, the
2023 emissions intensity was 867 lbs./MWh compared to the 2019-2023 average of 702
lbs./MWh. The future forecast shows a substantial decline at 340 lbs./MWh in 2026 to
100 Ibs./MWh by 2045. The 2045 intensity of emissions is 86% lower than the 5-year
average. With this method the annual emissions rate percentage is reduced more than
the total emissions due to the reductions from serving more load with a cleaner mix of
energy resources.
The last emissions profile for the resource portfolio includes other major air emissions
from Avista's generation plants. These emissions are well below air quality standards set
by the air regulatory agencies and are controlled and monitored at the plant level with the
best available technologies at the time of construction or modification. Avista tracks the
four major air emissions in the IRP shown in Figure 2.11: Nitrous Oxide (NOx), Sulfur
Dioxide (S02), Mercury (Hg),15 and Volatile Organic Compounds (VOCs) at owned or
controlled plants. After Colstrip leaves the portfolio in 2025, air emissions levels are
minimal by using natural gas generation with run time limitations on generators or by
emissions control systems. Kettle Falls is the only remaining facility with material air
emission levels from wood waste burning. The reason for the 2045 emission increase is
15 Avista does not track mercury emissions at natural gas facilities since it is not a permit requirement, the
emissions beyond 2025 are for Kettle Falls based on historic emissions intensity rates, although the most
recent study conducted after the IRP modeling was complete, indicated them as non-detectable. For
Colstrip, a default emission factor is used for mercury emissions.
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Chapter 2: Preferred Resource Strategy
due to additional biomass generation at Kettle Falls for increased capacity from a second
unit being added to the plant.
Beyond wood waste emissions, the plan includes burning both ammonia and hydrogen
in combustion turbines. Both fuels have NOx emission controls and adhere to air quality
limits but will still have non GHG air emissions. For existing and potential plants selected
to serve Washington customers, a non-energy impact of these emissions was considered
in the economic evaluation.
Figure 2.11: System Greenhouse Gas Emissions Intensity
1,000
900
800
700
0
J
— 600
PRS Forecast
500
� 2023 Generated Emissions
a400 340 5-Yr Avg.Generated Emissions
0 303 294 276 311
:2 300
222 200 189 182 183 169 166 160 162 178 170
200 144 142 136
100
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LO
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O CD CD CD CD CD CD CD CD CD CD CD O
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Chapter 2: Preferred Resource Strategy
Figure 2.12: Avista Owned and Controlled GeneraLiiig Plant Air Emissiuilb
800 NOX 10 S02
700
a
600 N 7
N N
c 500 6
c o
400 ~ 5
U U
4
300 N
3
200
2
100 1
N N N N M M M M M M M M M M 7 7 a 7 7 7 N N N N M M M M M M M M M M 7 7 7 7 7 7
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
0.02
Mercury 45 voc
40
0.02 35
N
N uNi 30
c c
c 0.01 25
v v 20
15
0.01
10
' S
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
Risk Assessment
Future planning of resource adequacy requires consideration of many risks. Avista is
utilizing the risks identified by the November 2020 paper "Implications of Regional
Resource Adequacy Program on Utility Integrated Resource Planning"16 as a framework
to present how Avista manages these risks. While a current long-term resource deficit is
projected for 2030, the risks outlined below will inform Avista's ultimate identification of
resource needs.
Peak Demand Forecast
Avista's peak demand forecast is based on historical and forecasted future weather
conditions. While weather is unknown for future loads, there are other load risks to be
considered. Avista considers load changes from other risks in the scenario analysis
Chapter 10 — specifically related to the impacts of electrification and customer growth,
including the potential for energy intensive data centers to be located within Avista's
service territory. Avista developed several load scenarios described Chapter 3 to
understand the portfolio implications of load changes. If future loads are lower, there is a
financial risk, as the outcome is a more reliable system at likely higher costs. However, if
16 Implications of a regional resource adequacy program on utility integrated resource planning
https://www.westernenergyboard.org/wp-content/uploads/11-2020-LBN L-W I EB-regional-resource-
adequency-and-utility-integrated-resource-planning-final-paper.pdf.
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Chapter 2: Preferred Resource Strategy
future loads are higher, having an underbuilt system that cannot meet a higher load
scenario creates a risk of resource adequacy and reliability challenges.
The underlying solution in the scenario analysis to protect against short-term, higher-than-
expected loads, is to develop DR programs and a four-hour energy storage system as
they have the shortest construction requirement. If data center loads are extremely high
in the next 5 years, additional resources will be required, including solar with batteries
and potentially natural gas turbines. However, if Avista acquires resources to manage this
risk and loads do not materialize, then utility rates will be higher.
Demand-Side Resource Contributioi,
Avista includes demand-side resources as options when determining the amount and
type of resources needed to meet future demand. Demand-side resources may also
impact the net demand of the system prior to this inclusion; customer adoption is an
example of this. Chapter 6 discusses each of the Distributed Energy Resource (DER)
options included in this IRP, including energy efficiency, DR, include other DER
generation and storage options.
The focus of DER modeling within the IRP is to ensure supply-side resources are not
overbuilt. For example, rooftop solar may reduce Avista's summer energy needs, but
have a limited impact on winter loads. To address this risk, Avista includes an estimate
of incremental customer owned generation in its load forecast. The greatest uncertainty
or risk regarding demand-side resources is whether they will impact winter peak load
requirements. Given most DER additions today are solar, this risk is low. Avista does find
customer storage DR solutions may assist with meeting peak loads. Regardless, a small
portfolio risk remains in customer(s) willingness to develop storage solutions or
willingness to allow their energy storage to be used to meet system needs.
Power riani Keurement
Avista's Colstrip ownership will end December 31, 2025. Avista also plans for plant
retirements for each of its existing natural gas peaking generators and has proposed end
dates for its combined cycle combustion turbines (CCCTs) to serve Washington
customers. In this IRP, the ability of these resources to operate until their proposed end
date is a significant resource adequacy risk. Avista sees this potential risk for the
projected 2029 retirement of the Northeast CTs in the short term. If Northeast is forced to
retire earlier due to mechanical failure, given Avista's short-term projected capacity
position is near even, scenario analysis indicates an immediate need to acquire nearly 80
MW of energy storage to replace the lost capacity. However, if the Northeast facility can
continue operating beyond 203017, it would delay the need for replacement resources
only for a short time. While it is unlikely, the forced unavailability of another resource will
require an immediate replacement. To mitigate this risk, Avista could begin to invest in
" Northeast's air permit expires December 31, 2032.
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Chapter 2: Preferred Resource Strategy
the development of multiple technologies to be ready and available for construction if
resources are retired early and to mitigate the high load risk discussed earlier.
,.�newable Contribution
In 2035, 125 MW of wind is expected to be available to meet winter peak load. Of the
1,200 MW of wind capacity, this translates to a 10% QCC, with a majority of this benefit
(76 MW) from the Montana portion of the wind portfolio. While wind in Montana has high-
capacity factors in winter months, these facilities are known to be unavailable when
temperatures are too cold. The region witnessed this phenomenon in January 2024.
Given this risk, Avista could see a planning capacity deficit if the wind turbines cannot
operate during cold weather events or if more reliable capacity is not built.
To help mitigate this risk, participating in the transmission line to North Dakota could
provide another market to purchase power — gaining access to this region of the country
with different load and weather conditions. One risk mitigation effort would be to reduce
the QCC of wind resources in winter periods resulting in additional capacity resource
selection. Avista expects the Western Resource Adequacy Program (WRAP) process,
administered by the Western Power Pool, will continue to monitor the performance of
wind in cold weather events and anticipates a future revision to winter QCCs. Additionally,
another risk for the wind QCCs revolves around the summer contribution if temperatures
are too high and there is a potential need for wind facilities to curtail generation. Given
the climate of Avista's service territory, the last mitigation effort is to ensure any future
wind technology Avista acquires must have suitable weather protection packages for
year-round operations, but these weather packages may still not be enough to meet the
most extreme temperatures seen in Montana winters.
Storage ttticiency
Given the PRS, storage efficiency is not a short-term risk to the utility. In the long-term
and under different future scenarios, however, this risk could materialize. Avista sees two
risks for storage efficiency. The first risk is similar to the renewable QCC contribution,
described above, where short duration resources may help improve reliability in small
increments. But the need to recharge the storage device after every use reduces its
reliability benefit. In this IRP, if the region does not develop enough sustainable and
dispatchable resources, the method to mitigate this risk is to reduce QCC values for short
duration storage over time.
The second risk of energy storage is the efficiency to recharge the device. Not all storage
technologies have the same recharging capability based on energy losses and time to
recharge. Therefore, these considerations should be considered when determining each
device's credit toward meeting peak demand. Avista's resource strategy includes new
energy storage technologies using renewable fuels, such as green hydrogen and
ammonia. These technologies protect against declining efficiencies found in today's
battery technology and offer longer duration periods. These resources have other risks
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Chapter 2: Preferred Resource Strategy
including technological risk (these are new and relatively unproven in large scale), and
they require significant energy to produce the fuel whereas the round-trip efficiency is less
than 25%.
Market Availability
In previous IRPs, Avista found market availability to be the greatest risk in resource
adequacy absent a resource adequacy market or program. Avista's previously performed
resource adequacy analysis assumed the utility was limited to 330 MW of market reliance
during a peak event. With the development of the WRAP, and the pending binding
requirements, Avista may be able to increase its market reliance threshold by adopting
lower PRM values compared with those used today. However, in today's environment
and reflected by the experience gained in the January 2024 winter peak event, it is clear
the regional market is limited in cold weather and drought conditions for our hydroelectric
resources. As witnessed in this recent event, the region was short of capacity and
imported 4,745 MW18 from outside the region during a time when transmission capability
was also limited. Given Avista's controlled load is 5-7% of the Northwest system, Avista
in theory could be allocated 240 MW to 300 MW of this import capability. Considering this
range for an actual event gives Avista confidence in the 330 MW assumption for market
access during a peak event.
Cost and Rate Projections
The IRP cost and rate projection does not include detailed forecasts beyond specific
generation acquisition, distribution, administrative, and Operations & Maintenance (O&M)
recovery costs. Rather, the IRP focuses on energy supply costs. Avista assumes these
non-generation costs increase by 3.8% per year to approximate an annual average
customer rate estimate using historic non-power supply cost growth rates. Further
resources are "priced" at levelized cost and may differ from actual revenue requirement
needs. Annual projected rates and revenue requirements are shown in Figure 2.13. Rates
are calculated by the total revenue requirement divided by retail sales and do not
represent rate class forecasts. Also, as future rates will be determined by actual
investments and evaluated by the Idaho and Washington commissions, this analysis
should only be used for comparative and informational purposes.
The projected Washington revenue requirement grows at 5.1% a year and rates increase
3.9% a year. Between 2040 and 2045, the revenue requirement and rates are estimated
to grow faster at 8.7% and 6.8% respectively. Future projected costs and rates for Idaho
are generally lower where the average revenue requirement grows at 3.6% each year
and rate increases are less at 3.1% annually.
'$Analysis of the January 2024 Winter Weather Event.pdf(powerex.com).
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Chapter 2: Preferred Resource Strategy
Figure 2.13: Projected Revenue Requirement and Rate Forecast by Stat(
3,000 0.300
WA Rev.Req. 0.248
ID Rev.Req.
2,500 _WA Rate 0.250
N —ID Rate
C
=
0.178 2,000 0.200
� t
C 0.133
G) 1,500 0.150 L
E d
d CL
-
�3
1,000 0.100
d'
N
500 0.050
d
0
LO I- 00 O O N M V LO O N_ 00 O O N Cl) V Ln
N N N N Cl) M Cl) Cl) Cl) Cl) CO Cl) Cl) M 7 7 7 It It
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
CETA's Cost Cap Considerations
Avista's resource strategy does not consider CETA's cost cap due to uncertainty of how
it will be applied. Given the PRS cost forecast, the only period when the cost cap could
be applicable is 2045. The cost cap is designed to limit compliance costs where
compliance is higher than a 2% cumulative investment each year as compared with a
resource portfolio not complying with the clean energy standard known as the Alternative
Lowest Reasonable Cost Portfolio. This portfolio is determined by placing a SCGHG on
the resource choices and includes previous CETA resource additions but excludes
CETA's clean energy targets. Lastly, the utility can only request to use the cost cap after
the compliance period has ended.
The 2% cost cap is based upon rates in the year prior to the compliance period and does
not account for the higher cost of compliance since the law began in 2019. Therefore, the
2% cost is a compounding higher rate and compares only the incremental societal costs
of the system but not the actual costs of the system. Given these challenges, it is nearly
impossible to estimate what the cost cap will be for the 2045 compliance period. It is also
unknown if the cost cap in this period will be spread over multiple compliance years or a
single year, or if it still applies. Lastly, CETA is mostly focused on meeting the
requirements through 2044. The 2045 target is a goal without statutory penalty for non-
compliance. Avista expects the legislature will address 2045 planning to meet this goal
over the next 10 years. Given the concern of hitting the cost cap in 2045, a portfolio in
Chapter 10 attempts to identify a future portfolio meeting a theoretical cost cap. The main
difference in this scenario is the cost constrained portfolio would retain Coyote Springs 2
as a natural gas facility with its full associated pro-rata generation capacity allocated to
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Chapter 2: Preferred Resource Strategy
Washington customers (rather than limiting its share to the hydrogen co-fire), avoiding a
second Kettle Falls unit.
Resiliency Metrics
As part of this plan, Avista measures other metrics rather than the emissions and costs,
these include job creation, energy burden, generation location, and many others. For
example, in Washington Customer Benefit Indicators (CBIs) are created to measure the
equitable transition to clean energy. These CBI metrics are available in the 2025 Clean
Energy Action Plan (CEAP). Avista added additional metrics for this plan to understand
the resiliency of our generation fleet.
RP-zmirrP Pnrtfnlin nivPrcity and RPciliPnm
In the TAC process resource diversity was discussed as a measure of resiliency. The
goal with this metric is to ensure Avista is not over reliant on one resource type or location.
Typically, resiliency is mentioned within the energy delivery system, but when it comes to
utility scale power generation, resilience is typically focused on the plants' ability to either
operate through or return to operation during an event. Another method to address this
potential risk is to have a more diversified resource portfolio. Figures 2.14 and 2.15 show
three metrics to measure diversity. Two of the measurements relate to locational diversity
for increasing resiliency, and the third is associated with fuel diversity of resources. These
metrics are split between winter and summer capacity, as both periods of time are key to
Avista's resource adequacy.
The diversity measurement uses the Herfindahl-Hirschman Index. The index is
traditionally used to determine market concentration or competitiveness, but in resource
planning it has also been used as a measure of resource diversity. Higher scores indicate
more concentration of resources, meaning less diversity as a share of the portfolio.
Conversely, the lower the score the more diverse the resource mix. From a market
concentration perspective, a score greater than 2,500 is highly concentrated and a score
below 1,500 is competitive, with scores between these amounts indicating moderate
levels of market concentration.
Fuel Sources
Fuel diversity is Avista's greatest resource risk. This measurement looks at the source of
the fuel for each generator. For example, the fuel source of Avista's Noxon Rapids
Hydroelectric project is the Clark Fork River, and the source of Palouse Wind is eastern
Washington Wind. For each of Avista's resources, a fuel source is identified. The
calculation is high due to the amount of Clark Fork Hydro reliance and Gas Transmission
Northwest (GTN)fuel delivery reliance for the Company's natural gas CTs. The index falls
(blue line, Figures 2.14 and 2.15) in 2041 due to the expiration of the Lancaster PPA as
replacement resources do not use GTN fuel.
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Chapter 2: Preferred Resource Strategy
Facility(Interconnection Point)
Avista has many small and large generators, but due to the large number of resources,
this index (orange line, Figures 2.14 and 2.15) is relatively diverse in total, and results in
the lowest score of the three diversity and resiliency metrics evaluated. This
measurement could also be related to shaft risk — or the risk of losing one unit causing a
resource adequacy event due to its size in relation to total load. Even though this
measurement is low, compared to the Company's peer utilities, Avista has one of the
highest shaft risks as a percentage of load. Due to this risk, Avista uses its single largest
shaft (Coyote Springs 2) as its minimum planning margin quantity for summer capacity
planning (16% in the summer).
Transmission (Geographic)
The last metric (green line, Figures 2.14 and 2.15) considered in this analysis is facility
location and this metric relates to the location of the resource. The result of this metric is
near the limit of concentration. This is due to the concentration of resources limited to a
few locations across Avista's small service area. Avista's largest location risk resource is
the Noxon Rapids and Cabinet Gorge area. To mitigate risks of transmission outages,
Avista developed multiple transmission pathways from this area to move energy to load.
The measurement was first discussed to mitigate risk from wildfire, whereas a more
diversified locational portfolio would be less impacted by wildfires. It's uncertain if this
metric can help assess wildfire risk.
Figure 2.14: Resource Diversity (Winter Capacity)
3,000
2,500
2,000
a�
L
0
U
c) 1,500
2
2
1,000
-Facility(interconnect point)
500 -Fuel (source)
-Transmission (geographic)
Lfl rl- 00 O O N CO LO CO � 00 M CDN M 'IT Ln
N N N N M M CO CO CO CO M CO M M �T It It �
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N N N N N N N N N N N N N N N N N N N N
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Chapter 2: Preferred Resource Strategy
Figure 2.15: Resource Diversity (Summer Capacity)
3,000
2,500
2,000
a�
L
O
V
cn 1,500
2
2
1,000
-Facility(interconnect point)
500 -Fuel (source)
-Transmission (geographic)
(0 t` 00 O O N M 't LO (0 r­ 00 0) CDN M ;t M
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Modeling Process
Avista utilizes a mixed integer optimization model to select supply-side and demand-side
resources to meet customer energy and capacity needs. Avista developed PRiSM to aid
in resource selection by using information from its hourly dispatch model, Aurora. PRiSM
evaluates each resource option's capital recovery, fixed operation costs, and non-energy
financial impacts relative to their operating margins from Aurora and the option's
capability to serve energy, peak loads, and clean energy obligations. PRiSM then
determines the lowest-cost mix of resource options meeting Avista's resource needs
using monthly granularity. The model can also measure and optimize the risk of various
portfolio additions when informed by Monte Carlo data. For this analysis, Avista includes
its forecast of 300 Monte Carlo market futures rather than a single forecast for its
evaluation. The PRS version of the PRiSM Excel workbook is publicly available in
Appendix G.
PRISM
Avista staff developed the first version of PRISM in 2002 to support resource decision
making in its 2003 IRP. The model continues to support the IRP as enhancements have
improved the model over time. PRiSM uses a mixed integer programming routine to
support complex decision making with multiple objectives. The results ensure optimal
values for variables given system constraints. The model uses an add-in function to Excel
from Lindo Systems named What's Best along with Gurobi's solver application. Excel
then becomes PRiSM's user interface. PRiSM simultaneously solves to meet system
reliability, energy obligations, and jurisdictional clean energy standards while minimizing
costs.
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Chapter 2: Preferred Resource Strategy
The model analyzes resource needs by state for Avista's entire system to ensure each
state will be assigned the appropriate amount of incremental costs (if any) of new
resource choices. PRiSM must satisfy deficits for each state and the system load and
resource balances for each month. For this IRP, the PRiSM model was enhanced to
include a simplified monthly natural gas Local Distribution Customer (LDC) model. This
model assists in determining the impacts of electrification of buildings. The model co-
optimizes solving for natural gas and electric demand allowing for the model to choose to
electrify load if the cost of natural gas service is too high. This enhancement was designed
for studying building electrification scenarios. This enhancement can also determine what
the total system cost impacts are if natural gas load is electrified.
The model solves using the net present value of utility costs given the following inputs:
1. Expected future deficiencies for each state and the system:
• Summer Planning Margin (16%, May through September)
• Winter Planning Margin (24%, October through April)
• Monthly energy targets by state including additional contingency
energy
• Monthly clean energy requirements
1. Costs to serve future retail loads as if served by the wholesale marketplace (from
Aurora)
• Existing resource and energy efficiency contributions
• Operating margins
• Fixed operating costs
• Capital costs
• Greenhouse Gas (GHG) emission levels
• Upstream GHG emission levels
• Operating GHG emissions
2. Supply-side resource, energy efficiency and demand response options
• Fixed operating costs
• Return on capital
• Interest expense
• Taxes
• Power/Gas Purchase Agreements
• Peak contribution from Western Resource Adequacy Program
(WRAP)/ E3 regional study
• Generation levels
• GHG emission levels for Climate Commitment Act (CCA)
• Upstream GHG emission levels (WA only)
• Construction and operating GHG emissions (WA only)
• Transmission/transport costs
3. Constraints
• Must meet energy, capacity, and Washington's clean energy shortfalls
without market reliance for each state
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Chapter 2: Preferred Resource Strategy
• Named Community Investment Fund minimum spending (WA only)
• Resource quantities available to meet future deficits
The model's operation is characterized by the following objective function:
Minimize: (WA "Societal" NPV2026-45) + (ID NPV2026-45) + (LDC Natural Gas
N PV2026-45)
Where:
• WA NPV2026-45= Market Value of Load + Existing & Future Resource
Cost/Operating Margin + Social Cost of Greenhouse Gas + Non-
Energy Impacts + Energy Efficiency Total Resource Cost
• ID NPV2026-45 = Market Value of Load + Existing & Future Resource
Cost/Operating Margin + Energy Efficiency Utility Resource Cost
Subject to:
• Resource availability and timing
• Energy efficiency potential
• Demand response potential
• Winter peak monthly requirements
• Summer peak monthly requirements
• Annual energy monthly requirements
• Washington's clean energy monthly goals
• Named Community Investment Fund outlays (WA only).
Avoided Cost
Avista calculates the avoided or incremental cost to serve customers by comparing the
PRS cost to alternative portfolios. Avista splits avoided costs between energy and
capacity to ensure the financial benefits are correctly attributed to the need of the system.
Avoided costs are useful to inform prices in new Public Utility Regulatory Policies Act
(PURPA) agreements, small resource acquisitions, and energy efficiency. As Washington
and Idaho have different energy policies, calculating costs requires an analysis of
incremental costs based on each state's specific policies. This portion of the chapter
estimates Avista's avoided cost of energy and capacity based on this IRP's portfolio
analysis. The calculations here are not used for setting Washington PURPA rates
provided in Schedule 62 but may inform its calculation. Specific Schedule 62 calculations
are in Appendix L.
Energy Efficiency
Washington's EIA requires utilities with more than 25,000 customers to acquire all cost-
effective and achievable energy conservation.19 These targets are also used for setting
19 The EIA defines cost effective as 10% higher cost than a utility would otherwise spend on energy
acquisition.
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Chapter 2: Preferred Resource Strategy
efficiency requirements in Washington's CEIP. For Washington, Avista uses the Total
Resource Cost (TRC)20 test plus non-energy impacts with a social cost of greenhouse
gas (SCGHG) savings to estimate its cost-effective energy savings, while Idaho uses the
Utility Cost Test (UCT). The estimated avoided cost of energy efficiency in Washington is
shown in Figure 2.16 and Idaho's is shown in Figure 2.17. The total 20-year Washington
energy avoided cost for energy efficiency is $74.21 per MWh and capacity is $170.24 per
kW-yr. These estimates do not include non-energy benefits, as these benefits are
program specific and will increase the avoided cost depending on whether the program
has non-energy impacts.
Idaho uses the UCT where the avoided cost is less due to the exclusion of clean energy
premiums, the Power Act21 preference, and avoidance of the social cost of GHG. Idaho
20-year energy avoided cost is $45.32 per MWh and capacity is$154.77 per kW-yr. Avista
includes the savings of future transmission and distribution expenses and line loss
savings in both states' avoided cost.
Figure 2.16: Washington Energy Efficiency Avoided Cost
Energy Value Capacity Value
$80 $180
$160 Preference,
$70 $15.48
SCGHG, Losses..$8.57
$20.89 j, $140
$60 TBD,
$25.38
$120
$50 Preference,$4.85
CDLo ses 2.6 p $100
N N
$40
N N $80
$30 d $60
J N
J
$20 $43.97 $40
$10 $20
$0 $0
20 See Chapter 5 for further information on the TRC and UCT methodologies.
21 Washington's EIA requires a 10% cost advantage adder for energy efficiency to give this resource
preference as required in the Northwest Power Act.
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Chapter 2: Preferred Resource Strategy
Figure 2.17: Idaho Energy Efficiency Avoided Cost
Energy Value Capacity Value
$140 $180
$120 $160
s Losses,$8.57
$140 T&o,
g $100 $25.38
i» Y $120
cli
o $80 0 $100
N
^' $60 N $80
GJ
> G1
J $40 a $60 Cap12 .
J
$40
$20
$20
$0 $0
Supply Avoided Costs
Avoided costs change as Avista's load and resource positions changes, as well as with
changes in the wholesale power market and new resource costs. Avoided costs are a
best-available estimate at the time of this analysis using the 2025 IRP assumptions. The
prices in Tables 2.7 and 2.8 represent energy and capacity values for different periods
and product types by state. For example, a new generation project with equal annual
deliveries in all hours has an energy value equal to the flat energy price.22 In addition to
the energy prices, these theoretical resources would also receive capacity payments for
production at the time of system peak. For this IRP, winter peak months are driving the
2030 resource deficit period.
Capacity value is the resulting average cost of capacity each year. Specifically, the
calculation compares a portfolio where the objective is to build only capacity resources to
meet only capacity requirements (excluding SCGHG) against a lower-cost portfolio with
no resource additions. Avista uses the jurisdiction's annual revenue requirement23
differences to create annualized costs of capacity beginning in the first year of a major
resource deficit. Recognizing the fluctuation of cash flows, the variability in annual values
is levelized and tilted using a 2% escalator. The next step divides the costs by added
capacity amounts during the winter peak. This value is the cost of capacity per MW or
cost per kW-year. The capacity payment applies to the capacity contribution of the
resource at the time of the winter peak hour. For Washington, the capacity requirements
calculation uses only clean resources to meet the capacity need.
22 Projects with undetermined energy production are estimated based on the resource's hourly production
forecast.
23 Transmission costs associated with new resources are included within the capacity cost. These include
the interconnection of the resource to the system and the cost to wheel power to Avista's customers.
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Chapter 2: Preferred Resource Strategy
Capacity pricing at the full capacity payment, shown in Tables 2.8 and 2.9, assumes a
100% QCC or Equivalent Load Carrying Capability (ELCC) in the winter. For example, if
solar receives a 2% QCC credit based on ELCC analysis, then it would receive 2% of the
capacity payment compared with its deliverable capacity. Avista will need to either
conduct an ELCC analysis or utilize the QCC value from the WRAP for any specific
projects it evaluates to determine its peak credit. The current forecast assumes Avista's
capacity deficit is higher in the winter than summer for all future years of the planning
horizon. While a mild winter and hotter than expected summer could result in an actual
summer peak greater than winter, Avista must continue to plan for extreme winter events
as experienced in January 2024.
VERs such as wind or solar, consume ancillary services because their output cannot be
forecasted with great precision. Consequently, VERs seeking avoided cost pricing may
receive reduced payments to compensate for ancillary service costs from Avista's VER
integration study.
In addition to the capacity premium, Avista includes an energy premium calculation similar
to the capacity credit but estimates the cost to comply with monthly energy targets of the
system. This adder is included for the first year of new resource additions. For
Washington, it corresponds to the first resource addition in 2029 and for Idaho in 2030.
This value is calculated by taking the difference between the PRS and a portfolio meeting
only state capacity deficits.
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Chapter 2: Preferred Resource Strategy
Table 2.8: Idaho New Resource Avowed Costs
Flat • • Capacit
Energy Energy Energy Premium Premiu
2026 $41.61 $42.50 $40.42 $0.00 $0.00
2027 $37.88 $37.26 $38.70 $0.00 $0.00
2028 $35.13 $33.57 $37.19 $0.00 $0.00
2029 $34.57 $33.01 $36.64 $0.00 $0.00
2030 $38.56 $36.84 $40.85 $4.46 $100.30
2031 $43.00 $40.96 $45.74 $4.55 $102.30
2032 $42.74 $40.36 $45.92 $4.64 $104.30
2033 $43.82 $41.29 $47.20 $4.73 $106.40
2034 $43.92 $41.19 $47.54 $4.82 $108.50
2035 $44.93 $42.18 $48.59 $4.92 $110.70
2036 $44.50 $41.72 $48.21 $5.02 $112.90
2037 $45.69 $42.61 $49.82 $5.12 $115.20
2038 $45.66 $42.64 $49.68 $5.22 $117.50
2039 $46.29 $43.19 $50.42 $5.33 $119.80
2040 $47.28 $43.96 $51.69 $5.43 $122.20
2041 $47.66 $44.19 $52.29 $5.54 $124.70
2042 $49.92 $46.35 $54.68 $5.65 $127.20
2043 $50.52 $46.88 $55.38 $5.77 $129.70
2044 $51.24 $47.58 $56.12 $5.88 $132.30
2045 $52.39 $48.71 $57.26 $6.00 $134.90
Levelized $42.77 $40.64 $45.60 $3.48 $78.20
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Chapter 2: Preferred Resource Strategy
Table 2.9: Washington New Resource Avoided Costs
Flat • • Capacity
Energy Energy Energy Premium Premium
2026 $41.98 $43.12 $40.46 $0.00 $0.00
2027 $38.14 $37.82 $38.58 $0.00 $0.00
2028 $35.40 $34.18 $37.03 $0.00 $0.00
2029 $35.04 $33.84 $36.64 $3.31 $0.00
2030 $39.18 $37.89 $40.90 $3.37 $132.30
2031 $44.10 $42.38 $46.40 $3.44 $135.00
2032 $44.33 $42.27 $47.09 $3.51 $137.70
2033 $45.40 $43.23 $48.29 $3.58 $140.40
2034 $45.55 $43.17 $48.72 $3.65 $143.20
2035 $46.71 $44.27 $49.96 $3.73 $146.10
2036 $46.40 $43.90 $49.74 $3.80 $149.00
2037 $47.66 $44.82 $51.45 $3.88 $152.00
2038 $47.77 $44.98 $51.51 $3.95 $155.00
2039 $48.48 $45.58 $52.35 $4.03 $158.10
2040 $49.59 $46.43 $53.79 $4.11 $161.30
2041 $50.01 $46.68 $54.44 $4.20 $164.50
2042 $52.31 $48.88 $56.90 $4.28 $167.80
2043 $52.97 $49.45 $57.66 $4.37 $171.20
2044 $53.84 $50.27 $58.61 $4.45 $174.60
2045 $55.07 $51.48 $59.83 $4.54 $178.10
Levelized $44.13 $42.27 $46.60 $2.87 $103.50
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Chapter 3: Economic and Load Forecast
3. Economic and Load Forecast
Avista's loads are an integral component of the Integrated Resource Plan (IRP). This
chapter summarizes the analysis methods and results of customer and load projections
between 2026 to 2045. The 2025 IRP utilizes a new load forecasting approach which
includes 3 phases: 1) the initial phase covers the first five years of the forecast and uses
econometric forecasting similar to prior plans, 2)the second phase calibrates with the first
five years and uses an end-use forecast model for the remaining years to forecast specific
customer uses of electricity, and 3) the final phase adjusts the long-term forecast for
monthly weatherization, line loss adjustments, and large industrial loads. In addition to
the expected case load forecast, multiple scenarios were also conducted to understand
effects to load due to population, electric vehicles, and building electrification.
Section Highlights
• The energy forecast grows at 0.91% per year as compared to 0.85% in
the 2023 IRP.
• Peak load growth is estimated at 1.32% in the winter and 1.09% in the
summer.
• In contrast to previous years, Avista used end-use modeling techniques
to develop the long-term load forecast.
• Avista expects a 214 aMW increase in load over the forecast period, a
400 MW increase in winter peak, and a 380 MW increase in summer peak
over the next 20 years.
• Increased building and transportation electrification adoption rates in both
Washington and Idaho could increase winter peak by 930 MW by 2045.
Medium-term Economic & Load Forecast
This section summarizes customer and load projections for the medium-term forecast.
This forecast covers the first five years of the IRP forecast (2024-2028).
conomic Characteristics
Avista's core electric service area includes more than a half million people residing in
Eastern Washington and Northern Idaho. Three Metropolitan Statistical Areas (MSAs)
dominate its service area: the Spokane and Spokane Valley, Washington MSA(Spokane-
Stevens counties); the Coeur d'Alene, Idaho MSA (Kootenai County); and the Lewiston-
Clarkson Idaho-Washington, MSA (Nez Perce-Asotin counties). These MSAs account for
more than 70% of both Avista's customers (i.e., meters) and load. The remaining 30%
are in low-density rural areas in both states. Washington accounts for approximately two-
thirds of electric customers and Idaho the remaining one-third.
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Chapter 3: Economic and Load Forecast
Population
Population growth is increasingly a result of net migration to Avista's service area as more
people move here. Net migration is strongly associated with both service area and
national employment growth through the business cycle. The regional business cycle
follows the U.S. business cycle, meaning regional economic expansions or contractions
follow national economic trends.24 Econometric analysis shows when regional
employment growth is stronger than U.S. growth over the business cycle, it is associated
with increased in-migration and the reverse holds true. Figure 3.1 shows annual
population growth since 1971 and highlights the recessions in yellow. During all deep
economic downturns since the mid-1970s, reduced population growth rates in Avista's
service territory led to lower load growth.25 The Great Recession reduced population
growth from nearly 2% in 2007 to less than 1% from 2010 to 2013. Accelerating service
area employment growth in 2013 helped push population growth above 1% after 2014.
Figure 3.1: MSA Population Growth and U.S. Recessions, 1971-2023
3.5%
3.0%
2.5%
2.0%
r
p 1.5%
C9
1.0%
c
e
Q 0.5%
0.0%
-0.5%
-1.0%
M A f\ O M LO h O M N ti O M LO � O M LA m M
f` h r` r- r` W W W W W O O O O m O O O O O N N
O O O O � O O O O O O O O O O OO O O O O O m O O
N N N N N N N N N N N
U.S. Recessionary Periods �Avista WA-ID MSAs Population Growth
24 An Exploration of Similarities between National and Regional Economic Activity in the Inland
Northwest, Monograph No. 11, May 2006. http://www.ewu.edu/cbpa/centers-and-
institutes/ippea/monograph-series.xml.
25 Data Source: Bureau of Economic Development, U.S. Census, and National Bureau of Economic
Research.
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Chapter 3: Economic and Load Forecast
Figure 3.2 shows population growth since 2012.26 Service area population growth
between 2010 and 2012 was lower than the U.S.; however, it was closely associated with
the strength of regional employment growth relative to the U.S. over the same period. The
same can be said for the increase in service area population growth in 2014 relative to
the U.S. population growth. The association of employment growth to population growth
has a one-year lag. The relative strength of service area employment growth in year "y"
is positively associated with service area population growth in year "y+1". Econometric
estimates using historical data show when holding the U.S. employment-growth constant,
every 1% increase in service area employment growth is associated with a 0.4% increase
in population growth in the next year.
Figure 3.2: Avista and U.S. MSA Population Growth, 2012-2023
2.5%
■Avista WA-ID MSAs
■U.S. 2.0%
2.0% 1.9% 1.9%
1.8% 1.7%
1.6%
L
r.+
G1.5% 1.4%
1.2%
� 1.1
7
1.0% 0.9%
Q 0.9%
o.s% o.s% o.a% o.s% 0.8%
0.6 0.7/,
0.6%
0.5% 0.5
0.5% 0.a/ 0.a%
0.2%
0.0%
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Employment
Given the correlation between population and employment growth, it is useful to examine
the distribution of employment and employment performance since 2012. The Inland
Northwest is a services-based economy rather than its former natural resources-based
manufacturing economy. Figure 3.3 shows the breakdown of non-farm employment for
all three-service area MSAs from the Bureau of Labor and Statistics. Almost 70% of
employment in the three MSAs is in private services (69%), followed by government
(17%) and private goods-producing sectors (15%). Farming accounts for 1% of total
employment. Spokane and Coeur d'Alene MSAs are major providers of health and higher
education services to the Inland Northwest.
26 Data Source: Bureau of Economic Analysis, U.S. Census, and Washington State Office of Financial
Management.
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Chapter 3: Economic and Load Forecast
Figure 3.3: Avista's MSA Non-Farm Employment Breakdown by Major Sector,
2023
Local Government,)
11%
Private Goods
State Government, --Producing, 15%
4%
Federal Government,
2%
Private Service
Producing, .•.
6,_ -,A
Following the Great Recession, regional employment recovery did not materialize until
2013, when services employment started to grow.27 Service area employment growth
began to match or exceed U.S. growth rates by the fourth quarter 2014. Since the COVID-
19 induced recession in 2020, service area employment has more than recovered from
the losses resulting from the nationwide shutdowns. Figure 3.4 compares Avista's
Washington and Idaho MSAs and the U.S. non-farm employment growth for 2012 to
2023.
27 Data Source: Bureau of Labor and Statistics.
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Chapter 3: Economic and Load Forecast
Figure 3.4: Avista and U.S. Non-Farm Employment Growth, 2012-2023
5.5%
4.3% 4.2%
3.5% d
3.0% 29%
2% 2.3
2.0% 1.9%1.9% 1.9% 2.1% 18% 2.0% 2. 2.0% 1.9%
1.7% 1.6%
1.5% 1.3%
r 0.6%
3
0
L
0 -0.5%
c
c
Q -2.5%
■Avista WA-ID MSAs _3.89
-4.5% ■U.S.
-6.5% -6.0%
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Figure 3.5 shows the distribution of personal income, a broad measure of both earned
income and transfer payments, for Avista's Washington and Idaho MSAs.28 Regular
income includes net earnings from employment, and investment income in the form of
dividends, interest, and rent. Personal current transfer payments include money income
and in-kind transfers received through unemployment benefits, low-income food
assistance, Social Security, Medicare, and Medicaid.
Transfer payments in Avista's service area in 1970 accounted for 12% of the local
economy. The income share of transfer payments has nearly doubled over the last 40
years locally to 23%. Although 56% of personal income is from net earnings, transfer
payments still account for more than one in every five dollars of personal income. Recent
years have seen transfer payments become the fastest growing component of regional
personal income. This growth in regional transfer payments reflects an aging regional
population, a surge of military veterans, and the lingering impacts of the COVID-19
transfer payments to households, including enhanced unemployment benefits.
Figure 3.6 shows the real (inflation adjusted) average annual growth per capita income
by MSA for Avista's service area and the U.S. overall. Although between 1980 and 1990,
the service area experienced significantly lower income growth compared to the U.S.
because of the back-to-back recessions of the early 1980s according to the Bureau of
Economic Analysis. The impacts of these recessions were more negative in the service
area compared to the U.S., so the ratio of service area per capita income to U.S. per
28 Data Source: Bureau of Economic Analysis.
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Chapter 3: Economic and Load Forecast
capita income fell from 93% in the 1970s to around 85% by the mid-1990s. The income
ratio has not recovered.
Figure 3.5: MSA Personal Income Breakdown by Major Source, 2022
Transfer
Receipts,23F, Net Earnings,
Dividends,
Interest,and
Rent, 19% Irr
Figure 3.6: Avista and U.S. MSA Real Personal Income Growth
3.0%
■Avista WA-ID MSAs
■U.S.
2.3/0
�; 2.5% 2.4% ° 2. 2.3% 2 3%2.4%
� 2%
2.1%
2.0%
O
V
1.5% 1.3%
C
c
Q 1.0%
0.8% 0.8%
�a
0.5%
Q 0.5%
as
0.0%
-0.5%
1970 to 1980 1980 to 1990 1990 to 2000 2000 to 2010 2010 to 2021 2020 to 2022
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Chapter 3: Economic and Load Forecast
Overview of the Medium-Term Retail Load Forecast
As described above, the load forecast for the 2025 IRP was done in three phases. The
following section describes the first phase — the development of a medium-term forecast
for the period 2026-2029. The forecast serves as the basis for the second phase, an end-
use forecast for the remaining period 2029 to 2045.
The medium-term forecast is based on a monthly use per customer (UPC) forecast and
a monthly customer forecast for each customer class in most rate schedules.29 The load
forecast multiplies the customer and UPC forecasts. The UPC and customer forecasts
are generated using time-series econometrics, as shown in Equation 3.1.
Equation 3.1: Generating Schedule Total Load
F(kWht,Y,+j,$) = F(kWh/Ct,Y,+j,$) X F(Ct,Yc+j,$)
Where:
• F(kWht,y,+j,$) = the forecast for month t, year j = 1,...,5 beyond the current
year, yc ,for schedule s.
■ F(kWh/Ct,yC+j,S) = the UPC forecast.
• F(Ct,yC+j,S) = the customer forecast.
UPC Forecast Methodology
The econometric modeling for UPC is a variation of the "fully integrated" approach
expressed by Faruqui (2000) in the following equation:30
Equation 3.2: Use Per Customer Regression Equation
kWh/Ct,y,s = aWt,Y + flZt,Y + Et,Y
The model uses actual historical weather, UPC, and non-weather drivers to estimate the
regression in Equation 3.2. To develop the forecast, normal weather replaces actual
weather (W) along with the forecasted values for the Z variables (Faruqui, pp. 6-7). Here,
W is a vector of heating degree day (HDD) and cooling degree day (CDD) variables; Z is
a vector of non-weather variables; and F-t,y is an uncorrelated N(O,a) error term. For non-
weather sensitive schedules, W= 0.
The W variables are HDDs and CDDs. Depending on the rate schedule, the Z variables
may include real average energy price (RAP); the U.S. Federal Reserve Industrial
Production Index (IP); residential natural gas penetration (GAS); non-weather seasonal
dummy variables (SD); trend functions (T); and dummy variables for outliers (OL) and
29 For schedules representing a single customer, where there is no customer count and for street lighting,
Avista forecasts total load directly without first forecasting UPC.
30 Faruqui, Ahmad (2000). Making Forecasts and Weather Normalization Work Together, Electric Power
Research Institute, Publication No. 1000546, Tech Review, March 2000.
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Chapter 3: Economic and Load Forecast
periods of structural change (SC). RAP is measured as the average annual price
(schedule total revenue divided by schedule total usage) divided by the Consumer Price
Index (CPI), less energy. For most schedules, the only non-weather variables are SD,
SC, and OL. See Table 3.1 for the occurrence RAP and IP.
If the error term appears to be non-white noise, then the forecasting performance of
Equation 3.2 can be improved by converting it into an (ARIMA) "transfer function" model
such that Ct,y = ARIMACt,y(p,d,q)(pk,dk,gk)k. The term p is the autoregressive (AR) order,
d is the differencing order, and q is the (MA) order. The term pk is the order of seasonal
AR terms, dk is the order of seasonal differencing, and qk is the seasonal order of MA
terms. The seasonal values relate to "k," or the frequency of the data, with the current
monthly data set, k = 12.
Certain rate schedules, such as lighting, use simpler regression and smoothing methods
because they offer the best fit for irregular usage without seasonal or weather-related
behavior, are in a long-run steady decline, or are seasonal and unrelated to weather.
Over the 2024-2028 period, Avista defines normal weather for the load forecast as a 20-
year moving average of degree-days taken from the National Oceanic and Atmospheric
Administration's Spokane International Airport data. Normal weather updates only occur
when a full year of new data is available. For example, normal weather for 2018 is the 20-
year average of degree-days for the 1998 to 2017 period; and 2019 is the average of the
1999 to 2018 period. This medium-term forecast uses the 20-year average from the 2004
to 2023 period to develop the 2024 to 2028 forecast.
The choice of a 20-year moving average for defining normal weather reflects several
factors. First, climate research from the National Aeronautics and Space Administration's
(NASA) Goddard Institute for Space Studies (GISS) shows a shift in temperature starting
almost 30 years ago. The GISS research finds summer temperatures in the Northern
Hemisphere increased one degree Fahrenheit above the 1951-1980 reference period;
the increase started roughly 30 years ago in the 1981-1991 period.31 An in-house analysis
of temperature in Avista's Spokane/Kootenai service area, using the same 1951-1980
reference period, also reflects an upward shift in temperature starting about 30-years ago.
As provided in Chapter 5, the longer-term temperature assumption in the IRP uses the
Representative Concentration Pathways (RCP) 8.5 for June, July, August, and
September, and the RCP 4.5 for the remainder of the year.
The second factor in using a 20-year moving average is the volatility of the moving
average as a function of the years used to calculate the average. The 10 and 15-year
moving averages show considerably more year-to-year volatility than the 20-year moving
average. This volatility can obscure longer-term trends and leads to overly sharp changes
in forecasted loads when applying the updated definition of normal weather each year.
31 See Hansen, J.; M. Sato; and R. Ruedy (2013). Global Temperature Update Through 2012,
http://www.nasa.gov/topics/earth/features/2012-temps.html.
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Chapter 3: Economic and Load Forecast
These sharp changes would also cause excessive volatility in the revenue and earnings
forecasts.
As noted earlier, if non-weather drivers appear in Equation 3.2, then they must also be in
the five-year forecast used to generate the UPC forecast. The assumption in the five-year
forecast is for RAP to be constant through 2028.
Table 3.1: UPC Models Using Non-Weather Driver Variables
VariablesSchedule
Washington:
Residential Schedule 1 GAS Ratio of natural gas residential schedule 101
customers in WA to electric residential
schedule 1 customers in WA.
Industrial Schedules 11, 21, and 25 IP
Idaho:
Residential Schedule 1 GAS Ratio of natural gas residential schedule 101
customers in ID to electric residential
schedule 1 customers in ID.
Industrial Schedules 11 and 21 IP
The forecasts for GDP reflect the average of forecasts from multiple sources including
the Bloomberg survey of forecasts, the Philadelphia Federal Reserve survey of
forecasters, the Wall Street Journal survey of forecasters and other sources. Averaging
forecasts reduces the systematic errors of a single-source forecast and assumes
macroeconomic factors flow through the UPC in the industrial rate schedules. Figure 3.7
shows the methodology for forecasting IP growth. Figure 3.8 shows the historical
relationship between the IP and industrial load for electricity.32,33 The load values used in
Figure 3.8 have been seasonally adjusted using the Census X11 procedure. Over the
long run, the historical relationship is positive between industrial load growth and IP
growth. However, the sensitivity of industrial loads to IP expansions weakened after. It's
unclear if this is a longer-term trend or something more temporary, like the 2002-2007
period of flat load growth with surging IP. In contrast, Avista's industrial load growth has
consistently fallen in response to recessions.
32 Data Source: U.S. Federal Reserve and Avista records.
33 Figure 3.8 excludes one large industrial customer with significant load volatility.
Avista Corp 2025 Electric IRP 97

Chapter 3: Economic and Load Forecast
Figure 3.7: Forecasting IP Growth
Average GDP U.S Industrial Production Generate Average, High, and Low
Growth Forecasts: Index(IP)Growth Model: IP Forecast:
• IMF, FOMC, • Model links year y Forecast annual IP growth
Bloomberg,etc. GDP GDP growth year y IP using the GDP forecast
• Average growth.
IP average(the baseline
forecasts out 5- • Federal Reserve scenario), a"high"scenario,
yrs. industrial production and a"low"scenario.
index is measure of IP The high and low GDP
growth. forecasts are the annual high
• Forecast out 5-years. and low values from the
sources used to generate the
average GDP growth rate in
each year.
• Apply scenario that makes
most sense given the most
current economic analysis.
• Convert annual growth
scenario to a monthly basis to
project out the monthly level of
the IP.
Figure 3.8: Industrial Load and Industrial (IP) Index
130
110
120
V 100
110 V Pr' ��' c
0
y M 90
100 II V h�I '� a
r o
�, 1�4� ., iJ 80
15
0
J 90 II� 70
-Industrial,SA V
80 Industrial,Trend-Cycle 60
-Industrial Production
70 50
N M M 7 � N (O I� r W O m 0 N M M 7 iA if1 c0 h I� W O m 0 � N M M
O m m O m O O O O O O O O O O O O O O O N N N N N N
c aT c a >. c aT c a T c aT c aT c a > c a T c a T c O_ T c OQ T C O_ T c O.
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Chapter 3: Economic and Load Forecast
Customer Forecast Methodology
The econometric modeling for the customer models ranges from simple smoothing
models to more complex autoregressive integrated moving average (ARIMA) models. In
some cases, a pure ARIMA model without any structural independent variables is used.
For example, the independent variables are only the past values of the rate schedule
customer counts but are also the dependent variable. Because the customer counts in
most rate schedules are either flat or growing in a stable fashion, complex econometric
models are generally unnecessary for generating reliable forecasts. Only in the case of
certain residential and commercial schedules is more complex modeling required.
For the main residential and commercial rate schedules, the modeling approach needs
to account for customer growth between these schedules with a high positive correlation
over a 12-month period. This high customer correlation translates into a high correlation
between residential and commercial customer growth over the same 12-month period.
Table 3.2 shows the correlation of customer growth between residential, commercial, and
industrial consumers of Avista's electricity and natural gas. To assure this relationship in
the customer and load forecasts, the models for the Washington and Idaho Commercial
models use Schedules 11 , while Washington and Idaho Residential models use Schedule
1 as a forecast driver. Historical and forecasted Residential Schedule 1 customers
become drivers to generate customer forecasts for Commercial Schedule 11 customers.
Table 3.2: Customer Growth Correlations, 1998-2023
(AnnualCustomer Class Residential Commercial Industrial Streetlights
Residential 1.00
Commercial 0.72 1.00
Industrial -0.29 -0.02 1.00
Streetlights -0.19 -0.06 -0.03 1.00
Figure 3.9 shows the relationship between annual population growth and year-over-year
customer growth.34 Customer growth has closely followed population growth in the
combined Spokane/Kootenai MSAs over the last 20 years. Population growth averaged
1.3% over the 2000-2023 period and customer growth averaged 1.2% annually.
Figure 3.9 demonstrates how population growth is the primary driver of customer growth.
As a result, forecasted population growth is the primary driver of Residential Schedule 1
customers in Washington and Idaho. The forecast is made using an ARIMA times-series
model for Schedule 1 customers in Washington and Idaho.
34 Data Source: Bureau of Economic Analysis, U.S. Census, Washington State OFM, and Avista records.
Avista Corp 2025 Electric IRP 99

Chapter 3: Economic and Load Forecast
Forecasting population growth is a process that links U.S. Gross Domestic Product (GDP)
growth to service area employment growth and then links regional and national
employment growth to service area population growth.
Figure 3.9: Population Growth vs. Customer Growth, 2002-2023
2.5%
■Avista WA-ID MSAs
System Customers
2.0°k
0 1.5%
t9
R �
Q 1.0% -
0.5%
0.0%
N CO V In (O f1 °° O O_ _ N M_ O N M
O O O O O O O O N N N N
O O O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N . N N N N N
The same average GDP growth forecasts used for the IP growth forecasts are inputs to
the five-year employment growth forecast. Avista averages employment forecasts with
S&P Connect (formerly IHS Connect)forecasts for the same counties. Averaging reduces
the systematic errors of a single-source forecast. The averaged employment forecasts
become inputs to generate population growth forecasts. Figure 3.10 summarizes the
forecasting process for population growth for use in estimating Residential Schedule 1
customers.
The employment growth forecasts (average of Avista and S&P Connect forecasts)
become inputs used to generate the population growth forecasts. The Spokane and
Kootenai forecast are averaged with S&P Connect's forecasts for the same MSA. These
averages produce the final population forecast for each MSA. These forecasts are then
converted to monthly growth rates to forecast population levels over the next five years.
Avista Corp 2025 Electric IRP 100

Chapter 3: Economic and Load Forecast
Figure 3.10: Forecasting Population Growth
Average GDP Regional Population Growth Models:
Growth Forecasts: • Model links regional, U.S., and CA year y-1
employment growth to year y county
• IMF, FOMC, Non-farm Employment population growth.
Bloomberg,etc. Growth Model: • Forecast out 5-years for Spokane,WA and
• Average Kootenai, ID.
forecasts out 5- Model links year y, y- • Averaged with S&P forecasts in ID and WA.
years. 1, and y-2 GDP • Growth rates used to generate population
growth to year y forecasts for customer forecasts for
regional employment residential schedule 1.
GDP growth.
• Forecast out 5-
years. EMP
• Averaged with S&P
forecasts.
Monthly Peak Load Forecast Methodology
The IRP's main requirement is to ensure enough resources are available to meet
resource adequacy needs, especially in the coldest and hottest days. Avista develops an
estimated peak load for each month and a seasonal peak as part of the load forecast.
The estimated regression Equation 3.3 is used to generate the starting seasonal peak
values for 2024. These starting peak values are extrapolated out over time by applying
an average annual growth rate over the forecast horizon. The annual growth rates are
provided by Applied Energy Group (AEG) as part of the end use forecast to be discussed
below. The process of generating the starting peak values follows:
• Historical data going back to 2004 is used to estimate the regression
coefficients shown in Equation 3.3. Diagnostic checks are done to
ensure the estimated error term from the regression on historical data
meets the assumptions that it should be uncorrelated over time and
be approximately N(0, o).
• Using actual weather data by month, the hottest average summer day
in a given year and coldest average winter day in a given year is
extracted from the average temperature time-series. These summer
and winter series reflect two subset series reflecting extreme
temperatures.
• Using the subset series of temperature extremes, the average
extreme temperature for summer months is calculated using the 20-
year period, 2004-2023 (i.e., an average based on n = 20). For winter
months, the average extreme temperature is calculated using the 76-
year period, 1949-2024. The differing sample size between summer
and winter reflects warming summers, if included older summer
temperatures the forecast would be biased down. In the winter,
temperature anomalies are still heavily skewed to very low
temperatures. Therefore, allowing a longer winter average reduces
the risk of under allocating peak resources for winter peak.
Avista Corp 2025 Electric IRP 101

Chapter 3: Economic and Load Forecast
• The 20-year summer average and 76-year winter average are
converted into degree days (CDD for summer and HDD for winter)
using a 65-degree Fahrenheit base. For the starting summer net
peak, the CDD value is entered into Equation 3.3 with appropriate
values for the remaining values. The same is done for HDD to arrive
at the starting winter peak for net peak for 2024/2025.
• Using the full starting peak native load values, peak growth rates
provided by AEG's end use forecast are used to escalate the starting
values over the IRP's forecast horizon.
Equation 3.3: Peak Load Regression Model
hMWd ty eak = A0 + a.1HDDd,t�y + A2(HDDd�t�y)2 + a3 HDD
d-1,t,y +
A4CDDd t,y + AsCDDd t y+ A6CDDd-1,t,y + (P1GDPt.y-1 + (P2(DSUM - GDPt.y-1)+(P3(DWIN
GDPt.y-1) + (')WDDd,t,y + (")HDDd,t,y + (HSDDt,y + (I)COVIDDJan 2022T=1 + O)OLDMar 2005=1 +
Ed,t,y f or t,y =June 2004 T
Where:
• hMW1etpeak = metered peak hourly usage on day of week d, in month
d,t,y
t, in year y, and excludes two large industrial producers and special
peak adders for future EVs, solar, and natural gas restrictions. The
data series starts in June 2004.
• HDDd,t,y and CDDd,t,y = heating and cooling degree days the day before
the peak.
• (HDDd,t,y)2 = squared value of HDDd,t,y,HDDd-1,t,y and CDDd-1,t,y
heating and cooling degree days the day before the peak.
• CDDdty = maximum peak day temperature minus 65 degrees.35
• GDPt.y-1 = extrapolated level of real GDP in month t in year y-1.
• (Dsum * GDPt.y-1) = a slope shift variable for GDP in the summer
months, June, July, and August.
• (DWIN * GDPt.y-1) = a slope shift variable for GDP in the winter months,
December, January, and February.
• WWDDd t,y= dummy vector indicating the peak's day of week.
• WHDDd,t,y = dummy vector indicating the high peak hours 8 am, 9 am,
4 pm, 5 pm, 6 pm, and 7 pm.
• WSDDt,y= seasonal dummy vector indicating the month.
• O)COVIDDJan 2022T=1= dummy variable that controls for a step-up in peak
following the COVID pandemic starting in January 2022.
• WOLDMar 2005=1 = a dummy variable to control for an extreme outlier in
March 2005.
• E:d,t,y= uncorrelated N(0, Q) error term.
35 This term provides a better model fit than the square of CDD.
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Chapter 3: Economic and Load Forecast
Long-Term Load Forecast
Previous IRPs used regression modeling techniques to forecast future load for the entire
forecast period. These modeling techniques use load related data, such as temperature,
population, and GDP to forecast the future using past data relationships. Avista is
currently entering a period where past energy use patterns may not be a good prediction
of the future. EV use, building electrification, changes in long-run temperatures, new
energy efficiency efforts, and distributed energy resources are not present in the historical
data used for regression models, but will likely be part of the future. End-use modeling
addresses this issue by starting at the customer equipment level (EVs, heat pumps, etc.)
rather than using historical data. The system load forecast is the aggregation of
customers and their adoption rates of customer equipment. This approach allows
modification of specific equipment adoption rates based on customer preference,
economic considerations, and regulatory frameworks.
Avista contracted with AEG to assist with the end-use portion of the forecast utilizing the
load forecast model developed for the energy efficiency potential studies. Development
of the model began with a segmentation of Avista's electricity footprint to quantify energy
use by sector, segment, end-use application, and the current set of technologies used.
AEG utilized information from Avista, the Northwest Energy Efficiency Alliance (NEEA),
and other secondary sources, as necessary. AEG used its Load Management Analysis
and Planning tool (LoadMAPTM) version 5.0 to develop the end use model and the
resulting forecast. AEG developed LoadMAPTM in 2007 and has enhanced it over time,
using it for the Electric Power Research Institute (EPRI) National Potential Study and
numerous utility-specific forecasting and energy efficiency potential studies. Built in Excel,
the LoadMAPTM framework is both accessible and transparent and has the following key
features:
• Embodies the basic principles of rigorous end-use models (such as
EPRI's REEPS36 and COMMEND37) but in a more simplified,
accessible form.
• Includes stock-accounting algorithms to treat older, less efficient
appliance/equipment stock separately from newer, more efficient
equipment. Equipment is replaced according to the measure life and
appliance vintage distributions defined by the user.
• Balances the competing needs of simplicity and robustness. This is
done by incorporating important modeling details related to equipment
saturations, efficiencies, vintage, and the like, where market data is
available, and treats end uses separately to account for varying
importance and availability of data resources.
• Isolates new construction from existing equipment and buildings and
treats purchase decisions for new construction and existing buildings
separately.
36 Residential end-use energy planning system
37 Commercial-sector end-use planning system
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Chapter 3: Economic and Load Forecast
• Uses simple logic for appliance and equipment decisions. Other
models available for this purpose embody complex decision-choice
algorithms or diffusion assumptions. The model parameters tend to be
difficult to estimate or observe, and sometimes produce anomalous
results that require calibration or even overriding. The LoadMAPTM
approach allows the user to drive the appliance and equipment
choices year by year directly in the model. This flexible approach
allows users to import the results from diffusion models or to input
individual assumptions. The framework also facilitates sensitivity
analysis.
• Includes appliance and equipment models customized by end use.
For example, the logic for lighting is distinct from refrigerators and
freezers.
• Can accommodate various levels of segmentation. Analysis can be
performed at the sector level (e.g., total residential) or for customized
segments within sectors (e.g., housing type or income level).
• Can incorporate conservation measures, demand-response options,
combined heat and power, distributed generation options, and fuel
switching.
The model was calibrated to actual data for 2021 through 2023 and the medium-term
forecast for years 2024 through 2028.
Segmentation for Modeling Purposes
The market assessment first defines the market segments (building types, end uses, and
other dimensions) with relevance to the Avista service territory. The segmentation
scheme for this project is presented in Table 3.3.
Table 3.3: Overview of Avista Analysis Segmentation Scheme
F Model Inputs Description Key Sources
Customer growth Forecasts of new construction in Avista short term actuals and forecast
forecasts residential, commercial, and from the U.S. Energy Information
industrial sectors Administration Annual Energy Outlook
AEO economic growth forecast
Equipment purchase For each equipment/technology, Shipment data from AEO and
shares for baseline purchase shares for each efficiency ENERGY STAR
projection level; specified separately for AEO regional forecast assumptions
existing equipment replacement Appliance/efficiency standards
and new construction analysis
Utilization model Price elasticities, elasticities for Electric Power Research Institute's
parameters other variables (income, weather) REEPS and COMMEND models and
AEO 2021
With the segmentation scheme defined, AEG then performed a high-level market
characterization of electricity sales in the base year to allocate sales to each customer
segment. AEG used Avista data and secondary sources to allocate energy use and
customers to the various sectors and segments such that the total customer count, energy
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Chapter 3: Economic and Load Forecast
consumption, and peak demand matched the Avista system totals from billing data. This
information provided control totals at a sector level for calibrating LoadMAPTM to known
data for the base year.
Market Profile:
The next step was to develop market profiles for each sector, customer segment, end
use, and technology. The market profiles provided the foundation for the development of
the baseline projection. A market profile includes the following elements:
• Market size is a representation of the number of customers in the
segment. For the residential sector, it is the number of households. In
the commercial sector, it is floor space measured in square feet. For
the industrial sector, it is overall electricity use.
• Saturations define the fraction of homes or square feet with the various
technologies (e.g., homes with electric space heating).
• The unit energy consumption (UEC) or the energy use index (EUI)
describes the amount of energy consumed in 2022 by a specific
technology in buildings that have the technology. UECs are expressed
in kWh/household for the residential sector, and EUIs are expressed
in kWh/square foot for the commercial sector.
• Annual Energy Intensity for the residential sector represents the
average energy use for the technology across all homes in 2022 and
is the product of saturation and UEC. The commercial sector
represents the average use for the technology across all floor space
in 2022 and is the product of the saturation and EUI.
• Annual Usage is the annual energy use by an end-use technology in
the segment. It is the product of the market size and intensity and is
quantified in GWh.
• Peak demand for each technology, summer peak and winter peak, is
calculated using peak fractions of annual energy use from AEG's
Energy Shape library and Avista system peak data.
The market characterization and market profiles are presented in the report in Appendix
C.
RacPlinP PrniPr_+inr
The following describes the development of the baseline projection of annual electricity
use and peak demand for 2026 through 2045 by customer segment and end use without
new utility programs. The savings from past programs are embedded in the forecast, but
the baseline projection assumes past programs cease to exist in the future. Possible
savings from future programs are captured by the potential estimates. The projection
includes the known impacts of future codes and standards over the study timeframe. All
such mandates defined as of May 2024 are included in the baseline. The baseline
projection is the foundation for the load forecast. The load forecast is then developed
utilizing the following:
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Chapter 3: Economic and Load Forecast
• Current economic growth forecasts (i.e., customer growth, income
growth).
• Electricity and natural gas retail price forecasts.
• Trends in fuel shares and equipment saturations.
• Existing and approved changes to building codes and equipment
standards.
• Avista's internally developed short-term sector-level projections for
electricity sales.
• AEG's estimates of electrification from Avista's natural gas system.
Data Application for Baseline Projection
Table 3.4 summarizes the LoadMAPTM model inputs required for the baseline projection.
These inputs are required for each segment within each sector, as well as for new
construction and existing dwellings/buildings.
Table 3.4: Overview of Avista Analysis Segmentation Scheme
Dimension Segmentation Variable Description
1 Sector Residential, commercial, industrial
2 Segment Residential: single family, multifamily, manufactured
home, differentiated by income level
Commercial: small office, large office, restaurant,
retail, grocery, college, school, health, lodging,
warehouse, and miscellaneous
Industrial: total
3 Vintage Existing and new construction
4 End uses Cooling, lighting, water heat, motors, etc. (as
appropriate by sector
5 Appliances/end uses and Technologies such as lamp type, air conditioning
technologies equipment, motors by application, etc.
6 Equipment efficiency levels Baseline and higher-efficiency options as appropriate
for new purchases for each technology
The baseline also includes projected naturally occurring energy efficiency during the
potential forecast period. AEG's LoadMAPTm efficiency choice model uses energy and
cost data as well as current purchase trends to evaluate technologies and predict future
customer equipment purchase shares. AEG also models the adoption of electrification
measures for natural gas customers and includes the future effects of this additional
electric equipment stock in Avista's territory. The customer equipment purchase data
feeds into the stock accounting algorithm to predict and track equipment stock and energy
usage for each market segment.
Use of the Baseline Forecast in IRP
AEG has been providing energy efficiency potential assessments for Avista since 2010.
A new component of the partnership between AEG and Avista is that the end-use load
forecast is now used to inform Avista's official load forecast for this IRP. The ability to
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Chapter 3: Economic and Load Forecast
capture specific end-use load movement and changes over time has become critical to
Avista's understanding of the long-term changes to their load.
To facilitate IRP planning, AEG provided the hourly disaggregation of the annual end-use
load forecast from the LoadMAPTM model. AEG carefully calibrated the projection to
actual Avista system loads by month and hour from 2021-2023, then carried the average
of those monthly calibration factors forward throughout the forecast period to create a
long-term forecast with the greatest consistency with recorded history and Avista's short-
term forecast.
While the main LoadMAPTm engines run on an annual basis, AEG used a combination of
region-specific load shapes from the National Renewable Energy Laboratory's (NREL)
end use load profiles, Avista's load research data and engineering simulations to further
analyze the end-use loads at an hourly level. These load shapes were then calibrated to
Avista's seasonal loads and normalized so the value for each hour represents 1/8760t" of
the year. The energy from the baseline projection for each end use and technology was
applied to each shape to compute hourly profiles throughout the forecast period. Figure
3.11 presents the energy forecast for each end use category, and the percentage growth
over the forecast period.
Figure 3.11: Change in Energy Use by End Use, 2025-2045
1,600
1,400
1,200
1,000
CO
3 • 1
CO Water MUMMY.-V
800 Cooling&Ventilation: 1
N
SpaceCO
• 1
600
Q lie
Appliances, ••• Prep,&Refrigeration: 1
400
200 • • •
Industrial: 1
0
In GD r W O) O N M V In CO W O O N M V In
N N N N N M M M M M M M M M M V 7 V V V V
O O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N N
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Chapter 3: Economic and Load Forecast
An important component of the load forecast is building electrification. New customers
were modeled with new codes and standards favoring electric over natural gas heat. In
addition, existing customers were modeled with the option to replace existing gas space
or water heating equipment with electric alternatives, using purchase decision logic taken
from the US DOE's National Energy Modeling System. Gas-to-electric conversion costs
include the possibility of a panel upgrade and associated labor along with the tax benefits
form the Inflation Reduction Act (IRA), but do not include any state incentives (as these
are not known). The model compares the lifetime cost of ownership including upfront
costs and associated lifetime fuel costs. Figure 3.12 and Figure 3.13 show the gas
residential heating market transformation for the forecast period. In these forecasts, the
electric system will be adding the areas in green and blue as new loads.
Figure 3.12: Washington Residential Gas Heating Market Transformation
160,000
140,000
120,000
100,000
v
0
80,000
3
O
60,000
40,000
20.000
(O 1__ 00 O O N (M V W (o r` oo O O N Co -t Lf)
N N N N M M M M M ('') M (M M M V V V V rt -?
O O O O O O O O O O O O O O O O O O o 0
(V N N N N N N N N N N N N N N N N N N (J
■Gas Furnace Gas Boiler
■Dual-Fuel Heat Pump-AFUE 80% -Dual-Fuel Heat Pump-AFUE 95%
■ Air-Source Heat Pump(ENERGY STAR 6.1)- Furnace
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Chapter 3: Economic and Load Forecast
Figure 3.13: Idaho Residential Gas Heating Market Transformation
140,000
120,000
100,000
0 80,000
0
L
w
a
= 60,000
40,000
20,000
(0 fl- CO O O N M � M (O N 00 O O N M V LO
N N N N Cl) M M Cl) (M Cl) M (M n M V V V V V
O O O O O CO CO CO CO CO O CO CO O O O O O O O
N N N N N N N N N N N N N N N N N N N N
■Gas Furnace ■Dual-Fuel Heat Pump-AFUE 80% ■ Air-Source Heat Pump(ENERGY STAR 6.1)-Furnace
Load Forecast
The load forecast produced with the end use model does not address some aspects of
the final load forecast, both for energy and peak. The following additional analyses were
conducted to finalize the load forecast for the IRP analysis:
• Add large industrial loads,
• Add line losses occurring in the delivery of energy from a generator,
through the transmission and distribution system to the end customer,
• Peak and energy were adjusted for weather normalization.
Weather Normalizatior
Weather has a significant impact on load. The AEG model only uses data from 2021 to
2023 to establish weather for their model, therefore a secondary weatherization step was
conducted to accurately represent historical data and future weather forecasts. Avista
applies weather data on a monthly basis. Each forecast month uses the average of the
data from the same month for the previous 20 years, except in the case of winter peak
(uses a 76-year rolling average). This is done to capture the full range of possible
temperatures.
The energy forecast utilizes monthly HDDs and CDDs while the peak load model utilizes
daily average temperature. The first year of the forecast uses historical data, but each
subsequent year adds in forecasted weather and removes historical weather such that
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Chapter 3: Economic and Load Forecast
the last several years of the forecast is based entirely on forecasted weather, except in
the case of the winter peak since the 76-year period still includes historical values. The
energy forecast is adjusted by total number of monthly HDDs or CDDs, while peak is
adjusted according to the coldest or hottest daily average temperature for each month as
appropriate for the season. For planning purposes, winter peak is the lowest average
daily temperature in January and the summer peak is the warmest average day in August.
A seasonal peak for each year was developed in addition to the monthly peak values to
reflect extreme events occurring anytime in the season rather than a specific month. This
data takes the hottest or coldest day over the course of multiple months for each year, as
it cooler and/or in other months rather than using January and August exclusively. The
seasonal peak is used to validate the load forecast in reliability modeling and to compare
with historical peak values. As described in Chapter 5, Avista uses the climate forecast
data generated by the River Management Joint Operating Committee (RMJOC). Avista
uses the RCP 8.5 for the summer months (June, July, August, September) and RCP 4.5
for the remaining months of the year.
Load Forecast
After combining the medium-term, end-use forecast, and weather normalization, the
resulting load forecast is shown in Table 3.5 for the expected case's average annual
energy in average megawatts (aMW) as well as summer and winter peaks in megawatts
(MW). The forecast is for Avista's native load, referring to Avista's retail customers, and
does not include other loads within the transmission balancing authority published in
FERC or EIA data.
Table 3.5: Expected Case Energy and Peak Forecasts
Year Energy January August Peak
2026 1,165 1,816 1,837
2027 1,167 1,821 1,846
2028 1,166 1,819 1,850
2029 1,165 1,821 1,835
2030 1,165 1,814 1,863
2031 1,166 1,818 1,870
2032 1,168 1,825 1,878
2033 1,177 1,852 1,884
2034 1,188 1,898 1,902
2035 1,200 1,893 1,905
2036 1,211 1,901 1,909
2037 1,227 1,949 1,948
2038 1,246 2,003 1,990
2039 1,263 2,028 2,023
2040 1,282 2,058 2,063
2041 1,305 2,093 2,090
2042 1,321 2,117 2,119
2043 1,344 2,168 2,135
2044 1,366 2,233 2,191
2045 1,379 2,261 2,217
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Chapter 3: Economic and Load Forecast
Figure 3.14 presents the seasonal peak load forecast in comparison to historical peak
loads38 prior to 2022, where winter peaks were often less then summer peaks due to
moderate winter temperatures until December 2022 and January 2024. The Spokane
area's average coldest day used for planning is 40, whereas in December 2022 (-3° with
a low of -100) and January 2024 (-4° with a low of -100) were much colder than the 50th
percentile coldest day used for planning.39 The January 2024 event during Martin Luther
King Jr. holiday weekend would have been Avista's all-time peak as shown in Figure 3.14,
at a load of 1,981 MW, but industrial loads were curtailed resulting in an official peak load
of 1,869 MW. Avista's all-time peak was set during the heat dome event in June 2021,
with a peak load of 1,889 MW when temperatures were an average of 93' (high of 109°)
compared to the planning temperature of 84°.
Figure 3.14: History and Forecast Peak Loads
2,500
2,000
M 1,500 ••••
C1
d
1,000
500
.....Actual Winter
.....Actual Summer
2025 IRP Winter
2025 IRP Summer
0 (p yLO
O ^ COO N N N N N N CO N N N M M M M M O M CI) M V V V V V V
O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
The annual average growth rate for the energy forecast is 0.91% between 2026 and 2045,
going from 1,165 aMW to 1,383 aMW. The forecast steps up at the beginning of the
forecast period as the result of a new large industrial load as compared to 2023. The
forecast is then relatively flat until 2032 when the forecasted annual load increases at a
greater rate due to building and transportation electrification beginning to show an impact.
Also, as described above, Avista uses a 20-year rolling average temperature in its load
38 Historical peak load data is corrected for known curtailed load or demand response.
39 Avista planning margin cover loads when temperature vary from the 501h percentile.
Avista Corp 2025 Electric IRP 111

Chapter 3: Economic and Load Forecast
forecast, therefore forecasted temperatures, rather than actual historical temperatures,
have an increased impact on temperature dependent loads in the later years of the
forecast.
Figure 3.15: History and Forecast Annual Energy Demand
1,500
1,400
1,100
ce
1.000
900
800
700 •••••Actual Annual Average Energy
Forecasted Average Annual Energy
600
O ^ W O ON N N N N N N N N . M M CO CO CO M CO LO M M CO M � V V V 7 V
O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
Load Scenario Analysis
In addition to the expected case, additional load forecast scenarios were developed,
including:
• High growth: assumes higher customer/population growth than the
expected case.
• Low growth: assumes lower customer/population growth than the
expected case.
• RCP 8.5: uses RCP 8.5 for the winter months as part of the future
periods included in the forecast. RCP 8.5 temperature forecast
between 2026-2045 is included in the historical average temperature
calculation for peak load temperatures.
• Washington Building Electrification: This scenario reduces natural gas
demand each year to achieve an 80% reduction by 2045. Where 75%
of the gas energy is added to Avista's electric load, the remaining load
would be applied to other utilities.
• Washington Building Electrification and High EV forecast: This
scenario adds higher transportation electrification as compared to the
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Chapter 3: Economic and Load Forecast
previous scenario's building electrification adjustment. It also includes
electrifying an equivalent of 806,000 EVs in the Washington service
area by 2045 as compared to 560,000 EVs equivalent in the expected
case.
• System Building Electrification and High EV. This scenario is similar
to Washington only electrification scenario but includes Idaho building
and transportation electrification. In this scenario natural gas demand
lowers each year to achieve an 80% reduction by 2045. (90% of this
load is Avista electric load) and adding an equivalent of 300,000 EVs
by 2045 as compared to 65,000 in the expected case forecast.
Figures 3.16, 3.17, and 3.18 present the annual energy, summer peak, and winter peak
respectively for each of the load scenarios. Table 3.6 shows the incremental change
between the expected case and each scenario in 2045. Energy in the high growth
scenario is 19% higher than the expected case, while the low growth scenario is 10%
lower. Use of the RCP 8.5 temperatures for the entire year lowers annual energy by 1%.
This is due to higher temperatures during the winter months. Washington building
electrification increases annual energy use by 8% and EV use that is greater than what
is included in the expected case in Washington increases annual energy by 6%. The
largest increase is 29% of annual energy resulting from building electrification and high
EV use across the entire system, both Idaho and Washington. This scenario also
increases winter peak by 41%.
Figure 3.16: Scenario Comparison of Annual Energy (aMW)
1.900
Expected case
1,800 High Growth
Low Growth
1,700 RCP 8.5
WA Building Electrification
WA Building Electrification&High Evs
1,600 System Building Electrification and High EV
1,500
14 1,400
1,300
1,200
1,100
1.000
CO r- 00 O O N CO V `CO CO r 00 O O N CO V LO
CV N CV CV CO M cM CO M CO CO M n CO V V V V V V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
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Chapter 3: Economic and Load Forecast
Figure 3.17: Scenario Comparison of Winter Peak (MW)
3,500
-Expected case
-High Growth
Low Growth
RCP 8.5
3.000 WA Building Electrification
WA Building Electrification & High Evs
System Building Electrification and High EV
2.500
2.000
1.500
1.000
110 r- 00 0) o N m 1* Ln cD r, 00 0, O r-I N m Ln
N N N N m m m m m m m m m m -1 11 It qt qt
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
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Chapter 3: Economic and Load Forecast
Figure 3.18: Scenario Comparison of Summer Peak (MW)
2.800
-Expected case
-High Growth
2,600 -Low Growth
_RCP 8.5
2,400 TWA Building Electrification
=WA Building Electrification &High Evs
-System Building Electrification and High EV ool
2.200
2,000
000
1,800
1.600
1.400
1,200
1,000
CO r- CO O O N CO V LO (O r__ 00 O O N CO V LO
N N N N M M CO CO CO rM CO CO CO (0 �* V Zt 't
O O O O O O O O O O O O O O O O O O O O
Table 3.6: Incremental Difference between Expected Case and Scenario in 2045
S ario Annual Winter Peak Summer
High Growth +268 +357 +494
Low Growth -132 -258 -193
RCP 8.5 -13 -23 0
WA Building Electrification +107 +336 +21
WA Building Electrification & High EVs 1 +183 1 +456 1 +161
System Building Electrification & High EV 1 +401 +930 +325
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Chapter 3: Economic and Load Forecast
This Page is Intentionally Left Blank
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Chapter 4: Existing Supply Resources
4. Existing Supply Resources
Avista relies on a diverse portfolio of assets to meet customer loads, including owning
and operating eight hydroelectric developments on the Spokane and Clark Fork rivers. Its
thermal assets include ownership of five natural gas-fired projects, a biomass plant.
Avista also purchases energy from several independent power producers (IPPs) and
regional utilities.
Section Highlights
• Hydroelectric resources provide approximately half of Avista's winter
generating capability.
• Natural gas-fired plants continue to represent a fundamental element, both
currently and into the clean energy future to maintain system reliability for
Avista's generation portfolio.
• Avista will transfer its ownership of Colstrip Units 3 & 4 to NorthWestern
Energy on January 1, 2026.
• The 97.5 MW Clearwater Wind project in Montana is commercially
operational in September 2024.
Figure 4.1 shows how much annual energy may be generated on Avista's system. This
annual energy chart represents the generation potential as a percentage of total supply;
this calculation includes fuel limitations (for water, wind, and wood), maintenance, and
forced outages. On an annual basis, natural gas-fired generation can produce more
energy (48%) than hydroelectric (38%) because it is not constrained by river conditions.
Avista's resource mix changes each year depending on streamflow conditions and market
prices. Figure 4.2 shows how much generation capacity Avista can rely on during winter
and summer peak. This winter and summer capability is the share of total capability of
each resource type the utility can rely upon to meet winter(January)and summer(August)
peak load. Avista's largest energy supply in the peak winter months is from hydroelectric
at 55%, followed by natural gas-fired resources at 39%.
Avista reports its fuel mix annually in the Washington State Fuel Mix Disclosure.40 The
Washington State Department of Commerce calculates the resource mix used to serve
load, rather than its generation potential. The report includes estimates for regional41
market purchases without an identified energy source and Avista-owned generation
minus renewable energy credit (REC) sales. Figure 4.3 shows Avista's 2023 Fuel Mix
Disclosure for 2022 data. The Idaho fuel mix is nearly identical to Washington's except
for its allocation of Public Utility Regulatory Policies Act (PURPA) generation. Each state
40 11A-Utility-Fuel-Mix-Market-Summary-20240108.pdf from Washington Department of Commerce.
41 For 2022, the region is approximately 54% hydroelectric, 13% unspecified, 10% natural gas, 9% coal,
8% wind, 4% nuclear and 2% other. When Avista sells RECs from its resources the remaining generation
is assigned a fuel mix and an emissions level in the report equal to regional average emissions.
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Chapter 4: Existing Supply Resources
is allocated RECs based on their current authorized share of the system (approximately
65% Washington and 35% Idaho). Avista may retain RECs, sell them to other parties, or
transfer them between states. Avista transfers RECs from Idaho to comply with
Washington's Energy Independence Act (EIA). Idaho customers are compensated for the
value of RECs at market value whenever these transfers occur.
riyu,e 4.1: 2026 Annual Energy Capability (System)
Natural Gas
48%
Net
Contracted
Hydro
9%
Biomass,
Wind.Solar,F
&Refuse
14%
Figure 4.2: 2026 Avista System Seasonal Capability
Winter Peak Capability Summer Peak Capability
Natural Gas Natural Gas
39% Net
Contracted 33°%
Net Contracted Hydro18%
Hydro Biomass, Biomass,
11% Wind.Solar, Wind,Solar,
&Refuse &Refuse
• 6% • 6%
Hydro
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Chapter 4: Existing Supply Resources
Figure 4.3: Avista's Washington State ruei mix uisciosure
Other
Blogenic
1�0,_,, %
Natural Gas
34
Petroleum
Waste
■ 1%
;Hydro'
Biomass
oal 6
14%
Spokane River Hydroelectric Developments
Avista owns and operates six hydroelectric developments on the Spokane River. Five
operate under a 50-year Federal Energy Regulatory Commission (FERC) operating
license through June 18, 2059. The sixth, Little Falls, operates under separate
authorization from the U.S. Congress because of its location on tribal land. This section
describes the Spokane River hydroelectric developments and provides the maximum on-
peak and nameplate capacity ratings for each plant. The maximum on-peak capacity of
a generating unit is the total amount of electricity it can safely generate with its existing
configuration and the current mechanical state of the facility. Unlike other generation
assets, hydroelectric capacity is often above nameplate because of plant upgrades and
favorable head or streamflow conditions. The nameplate, or installed capacity, is the
original capacity of a plant as rated by the manufacturer. All six hydroelectric
developments on the Spokane River connect directly to the Avista transmission system.
rust rails
Post Falls is the hydroelectric facility furthest upstream on the Spokane River. It is located
several miles east of the Washington/Idaho border. The facility began operating in 1906
and during summer months maintains the elevation of Lake Coeur d'Alene. Post Falls
has a 14.75 MW nameplate rating but could produce up to 18.0 MW with its six generating
units.
In February 2024, Avista's Post Falls Hydroelectric Dam was selected for U.S.
Department of Energy grant funding, receiving a $5 million Hydroelectric Efficiency
Improvement Incentive for improvements to increase the facility's efficiency. The goal of
the Post Falls Modernization project is to replace existing aging equipment with modern,
energy-efficient designs and equipment, and increase the useful life of the facility. The
planned updates will not change operations nor capacity of the Post Falls dam and are
estimated to be complete in 2029.
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Upper Falls
The Upper Falls development is in downtown Spokane's Riverfront Park and began
generating in 1922. The project is comprised of a single 10 MW unit on the north channel
of the river.
Monroe Street
Monroe Street, Avista's first hydroelectric plant, began serving customers in 1890 in
downtown Spokane at Huntington Park. Following a complete rehabilitation in 1992, the
single generating unit has a 15 MW maximum capacity rating.
A private developer built the Nine Mile hydroelectric plant in 1908 near Nine Mile Falls,
Washington. Avista purchased the project in 1925 from the Spokane & Inland Empire
Railroad Company. Nine Mile has undergone substantial upgrades with the installation of
two new 8 MW units and two 10 MW units for a total nameplate rating of 36 MW.
Long Lake
The Long Lake development is located northwest of the City of Spokane and maintains
the Lake Spokane reservoir or Long Lake. The project's four units have a maximum
capacity of 88 MW of combined capacity.
Little Falls
The Little Falls development, completed in 1910 near Ford, Washington, is the furthest
downstream hydroelectric facility on the Spokane River. The facility's four units generate
35.2 MW. As Little Falls is partially located on the Spokane Indian Reservation, it was
congressionally authorized and is not under FERC jurisdiction. Avista operates Little Falls
Dam in accordance with an agreement reached with the Spokane Tribe in 1994 to identify
operational and natural resource requirements. Little Falls Dam is also subject to other
Washington State environmental and dam safety requirements.
Clark Fork River Hydroelectric Development
The Clark Fork River Development includes two hydroelectric projects located near Clark
Fork, Idaho, and Noxon, Montana, 70 miles south of the Canadian border on the Clark
Fork River. The plants operate under a FERC license through 2046 and connect directly
to Avista's transmission system.
Noxon .. ,F. —
The Noxon Rapids development includes four generators installed between 1959 and
1960, and a fifth unit that entered service in 1977. Avista completed major turbine
upgrades on units 1 through 4 between 2009 and 2012. The total capability of the plant
is 610 MW under favorable operating conditions, although Avista uses 555 MW for
planning purposes.
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Cabinet Gorge
Cabinet Gorge started generating power in 1952 with two units, and two additional
generators were added the following year. Upgrades to units 1 through 4 occurred in
1994, 2004, 2001, and 2007, respectively. The current maximum on-peak plant capacity
is 270.5 MW, modestly above its 265.2 MW nameplate rating.
Total Hydroelectric Generation
In total, Avista's hydroelectric plants have nearly 1,080 MW of capacity. Table 4.1
summarizes the location and operational capacities of Avista's hydroelectric projects, and
the expected energy output of each facility based on an 80-year hydrologic record.
able 4.1: Avista-Owned Hydroelectric Resources
Project Name River Location Nameplate Maximum Expected
System Capacity Capability Energy
�A (MW) (MW)_ (aMW)
Monroe Street Spokane Spokane, WA 15.0 15.0 11.2
Post Falls Spokane Post Falls, ID 14.8 18.0 9.4
Nine Mile Spokane Nine Mile Falls, WA 36.0 32.0 15.7
Little Falls Spokane Ford, WA 32.0 35.2 22.6
Long Lake Spokane Ford, WA 81.6 88.0 56.0
Upper Falls Spokane Spokane, WA 10.0 10.2 7.3
Noxon Rapids Clark Fork Noxon, MT 518.0 610.0 196.5
Cabinet Gore Clark Fork Clark Fork, ID 265.2 270.5 123.6
Total 1 972.E 1 1,078.9 442.3
Thermal Resources
Avista owns six thermal generation assets located across the Northwest. These assets
provide dependable energy and capacity serving base and peak-load obligations. Table
4.2 summarizes these resources by fuel type, online year, remaining design life, book
value at the end of 2025 and the last year of expected service for IRP modeling purposes.
Table 4.3 includes capacity information for each of the facilities along with the five-year
historical forced outage rates used for modeling purposes.
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Table 4.2: Avista-Owned Thermai Kesources
Project Location Fuel Start Last Year Book Value Book Life
Type Date of Service 42 (mill. $) (years)
Rathdrum Rathdrum, ID Gas 1995 2044 18.7 7.2
Northeast43 Spokane, WA Gas 1978 2029 0.0 0.0
Boulder Park Spokane, WA Gas 2002 2040 12.8 15.7
Coyote Springs 2 Boardman, OR Gas 2003 n/a 98.7 15.2
Kettle Falls Kettle Falls, WA Wood 1983 n/a 59.2 17.4
Kettle Falls CT Kettle Falls, WA Gas i 2002 2040 1.9 9.9
Table 4.3: Avista-Owned Thermal Resource Capability
Maximum Maximum Capacity (MW)Project Name Winter Summer Nameplate Forced
CapacityCapacity (MW)
Rathdrum 2 units 176.0 130.0 166.2 5.8
Northeast (2 units) 66.0 42.0 61.8 n/a
Boulder Park 6 units)- 24.6 24.6 24.6 10.5
Coyote Springs 2 317.5 286.0 306.5 3.8
Kettle Falls 47.0 1 47.0 50.7 12.3
Kettle Falls CT 11.0 8.0 7.2 2.7
Total 864.1 759.6 864.0
Rathdrum
Rathdrum consists of two identical simple-cycle combustion turbine (CT) units. This
natural gas-fired plant located near Rathdrum, Idaho connects to the Avista transmission
system. This facility entered service in 1995 and has a maximum combined capacity of
176 MW in the winter and 126 MW in the summer. The nameplate rating is 166.2 MW.
Chapter 7, Supply-Side Resource Options, provides details about upgrade options under
consideration at Rathdrum.
Northeas
The Northeast plant, located in Spokane, has two identical aero-derivative simple-cycle
CT units completed in 1978. The plant can burn natural gas and oil, but current air permits
preclude the use of fuel oil. The combined maximum capacity of the units is 66 MW in the
winter and 42 MW in the summer, with a nameplate rating of 61.8 MW. The plant air
permit limits run time to 50 hours per year, limiting its use to primarily serve reliability
events. For the purposes of this IRP, Avista assumes this plant will retire in 2030, but no
official retirement date has been set. The existing air permit for the Northeast plant expires
at the end of 2032.
42 The last year of service is estimated retirement or end of service for utility customers. This IRP assumes
Coyote Springs 2 to be ineligible for Washington in 2045, but still eligible to serve Idaho customers.
43 There is no remaining book life but there are five years of remaining tax depreciation impacts to
customers.
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Boulder Park
The Boulder Park project entered service in Spokane Valley in 2002. It connects directly
to the Avista transmission system. The site uses six identical natural gas-fired internal
combustion reciprocating engines to produce a combined maximum capacity and
nameplate rating of 24.6 MW. For modeling purposes of this IRP, Avista assumes this
plant will retire in 2040.
Coyote Springs ,
Coyote Springs 2 is a natural gas-fired combined cycle combustion turbine (CCCT)
located near Boardman, Oregon. The plant connects to the Bonneville Power
Administration (BPA) 500 kV transmission system under a long-term agreement. The
plant began service in 2003 and has a maximum capacity of 317.5 MW in the winter and
285 MW in the summer with duct burners operating. The nameplate rating of the plant is
287.3 MW.
Kettle Falls Generation Station and Kettle Falls Combustion Turbine
The Kettle Falls Generating Station entered service in 1983 near Kettle Falls,
Washington. It is among the largest biomass generation plants in North America and
connects to Avista on its 115 kV transmission system. The open-loop steam plant uses
waste wood products (hog fuel) from area mills and forest slash but can also burn natural
gas on a limited basis. A 7.5 MW combustion turbine (CT), added to the facility in 2002,
burns natural gas and increases overall plant efficiency by sending exhaust heat to the
wood boiler when operating in combined-cycle mode.
The wood-fired portion of the plant has a maximum capacity of 50 MW and a nameplate
rating of 50.7 MW. Varying fuel moisture conditions at the plant causes correlated
variation between 45 and 50 MW. The plant's capacity increases from 55 to 58 MW when
operated in combined-cycle mode with the CT. The CT produces 8 MW of peaking
capability in the summer and 11 MW in the winter. The CT can be limited in the winter
when the natural gas pipeline is capacity constrained.
.olsb iN
The Colstrip plant, located in eastern Montana, consists of two coal-fired steam plants
(Units 3 and 4) connected to a double-circuit 500 kV line owned by each of the
participating utilities. The utility-owned segment extends from Colstrip to Townsend,
Montana. BPA's ownership of the 500 kV line starts in Townsend and continues west.
Energy moves across both segments of the transmission line under a long-term wheeling
arrangement. Talen Montana, LLC operates the facilities on behalf of the six owners (see
Table 3.4). Avista currently owns 15% of Units 3 and 4. Unit 3 began operating in 1984
and Unit 4 in 1986. Avista's share of Colstrip has a maximum net capacity of 222 MW,
and a nameplate rating of 247 MW. On January 1, 2026, ownership of Colstrip will be
transferred to Northwestern Energy and therefore will no longer serve Avista customers.
NorthWestern will assume all of Avista's Colstrip ownership along with its related interest
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in the plant, plant equipment, rights, and obligations. Under the Agreement, Avista retains
its existing remediation obligations and enters into a vote sharing agreement
with NorthWestern to retain voting rights in regard to any decisions made with respect to
remediation activities.
Small Avista-Owned Solar
Avista operates three small solar projects. The first solar project is three kilowatts located
at its corporate headquarters. Second, Avista installed a 15-kilowatt solar system in
Rathdrum, Idaho to supply its My Clean EnergyTM (formerly Buck-A-Block) voluntary
green energy program. Lastly, Avista has a 423-kW Community Solar project, located at
the Boulder Park property, began service in 2015.
Table 4.4: Avista-Owned Solar Resource Capability
Project Name Project Location Project Capacity
Spokane Headquarters Solar Spokane, WA 4
Rathdrum Solar Rathdrum, ID 15
Boulder Park Solar Spokane Valley, WA 423
Total 442
Power Purchase and Sale Contracts
Avista uses purchase and sale arrangements of varying lengths to meet some of its load
requirements. These contracts provide many benefits by adding clean generation from
low-cost hydroelectric and wind power to the Company's resource mix. This section
describes the contracts in effect during the IRP. Tables 4.5 and 4.6 summarize Avista's
contracts.
Mid-Columbia Hydroelectric Contracts
During the 1950s and 1960s, Public Utility Districts (PUDs) in central Washington
developed hydroelectric projects on the Columbia River. Each plant was large compared
to loads served by the PUDs. Long-term contracts with public, municipal, and investor-
owned utilities throughout the Northwest assisted project financing by providing a market
for surplus power. The contract terms obligate the PUDs to deliver power to Avista points
of interconnection. Avista originally entered long-term contracts for the output of five
projects "at cost". Avista now competes in capacity auctions to retain the rights of these
contracts as they expire. The Mid-Columbia contracts in Table 4.5 provide clean energy,
capacity, and reserve capabilities.
Under the 1961 Columbia River Treaty and the 1964 Pacific Northwest Coordination
Agreement (PNCA), the Mid-Columbia projects optimize hydroelectric project operations
in the Northwest U.S. and Canada. In return for these benefits, Canada receives a share
of the energy under the Canadian Entitlement. The Columbia River Treaty and the PNCA
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manage water storage in upstream reservoirs for coordinated flood control and power
generation optimization. The Columbia River Treaty recently concluded negotiations in
July 2024. At this time, no specific information is available pertaining to the generation
impact, however it is expected less energy will be transferred to Canada under the
Canadian Entitlement.
Columbia Basin Hydro
In December 2022, Avista reached an agreement to purchase the entire output from
Columbia Basin Hydro's irrigation generation fleet through 2045. The agreement includes
all generation and environmental attributes from their seven hydroelectric projects totaling
146.3 MW of capacity. Avista will begin taking delivery of projects as existing contracts
with other utilities expire. Table 4.6 outlines the project delivery timeline, capacity, and
energy deliveries for Columbia Basin Hydro. These projects are unique as they are based
on the amount of irrigation used by central Washington farmers from March through
October, with most of the generation occurring in May through August in a consistent firm
energy delivery.
Table 4.5: Mid-Columbia Capacity and Energy Contracts44
Counter Project(s) Percent Start Date End Date On-Peak
CapabilityParty Share
Grant Priest Rapids/ 3.46 Dec-2001 Dec-2052 74.9 38.4 -1.4
PUD Wana um
Chelan Rocky Reach/ 5.0 Jan-2016 Dec-2030 87.5 52.4 -1.9
PUD Rock Island
Chelan Rocky Reach/ 5.0 Jan-2024 Dec-2033 I 87.5 52.4 -1.9
PUD Rock Island
Chelan Rocky Reach/ 5.0 Jan-2026 Dec-2030 87.5 52.4 -1.9
PUD Rock Island
Chelan Rocky Reach/ 10.0 Jan-2031 Dec-2045 174.9 104.8 -3.8
PUD Rock Island
Douglas Wells 1.5345 Oct-2018 Dec-2028 23.8 12.2 -0.4
PUD
44 For purposes of long-term transmission reservation planning for bundled retail service to native load
customers, replacement resources for each of the resources identified in Table 4.5 are presumed and
planned to be integrated via Avista's interconnection(s)to the Mid-Columbia region.
45 Percent share varies each year depending on Douglas PUD's load growth.
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Table 4.6: Columbia Basin Hyaro rrojects
Project Name Start Date Capacity
Russell D. Smith 1/1/2023 6.1 1.5
EBC 4.6 5/1/2023 2.2 0.9
Summer Falls 1/1/2025 94.0 41.4
PEC 66 3/1/2025 2.4 0.5
Quincy Chute 10/1/2025 9.4 3.6
Main Canal 1/1/2027 26.0 11.6
PEC Headworks 9/1/2030 6.2 2.3
Total 146.3 61.8
Public Utility Regulatory Policies Act (PURPA)
The passage of PURPA by Congress in 1978 required utilities to purchase power under
standardized contracts from resources meeting certain size and fuel criteria. As shown in
Table 4.7, Avista has many PURPA, or Qualifying Facility (QF) energy purchase
contracts, totaling 139.9 MW, with a five-year average output of 73 aMW. Avista also has
PURPA fully net metered generation from customer load shown in Table 4.8 for a total of
7.5 MW. Power from net metered facilities is only purchased if generation exceeds load.
Based on Avista's experience with these contracts and ongoing communications with the
project owners, the IRP assumes the renewal of these contracts after the term expires.
Avista takes the energy as produced, does not control the output of any PURPA
resources.
Table 4.7: PURPA Agreements
Fuel Source Location Contract Size 5 year
Date (MW) avg. Gen.
History
7777 1 11 (aMW)
Meyers Falls Hydro Kettle Falls, WA 12/2025 1.30 1.06
Spokane Waste to Energy Waste Spokane, WA 12/2037 22.70 13.63
Plummer Sawmill46 Wood Waste Plummer, ID 12/2025 5.80 3.00
Deep Creek Hydro Northport, WA 12/2032 0.41 0.02
Clark Fork Hydro Hydro Clark Fork, ID 12/2037 0.22 0.11
Upriver Dam47 Hydro Spokane, WA 12/2037 14.50 4.96
Big Sheep Creek Hydro Hydro Northport, WA 6/2025 1.40 0.82
Ford Hydro LP Hydro Weippe, ID 6/2026 1.41 0.36
John Day Hydro Hydro Lucile, ID 9/2041 0.90 0.24
Phillips Ranch Hydro Northport, WA n/a 0.02 0.00
City of Cove Hydro Cove, OR 10/2038 1 0.80 1 0.36
Clearwater Paper Biomass Lewiston, ID 12/2026 93.80 48.67
Total 143.26 73.23
46 The owner publicly announced it is shutting down the mill and generator and this resource is excluded
from this plan.
47 Energy estimate is net of the City of Spokane's pumping load. The City of Spokane owns this facility.
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Table 4.8: Net PURPA Agreements
Contract Fuel Source Location Contract Size
. D.
Spokane County Digester Biomass Spokane, WA 8/2030 0.26
Spokane Eco District48 Solar/BESS Spokane, WA 4/2039 1.00
Great Northern Solar Spokane, WA 5/2035 0.25
U of Idaho Steam Plant CHP Steam Moscow, ID 2/2042 0.83
U of Idaho Solar Solar Moscow, ID 2/2026 0.13
Vaagen Brothers Lumber49 Biomass Colville, WA 7/2039 5.00
Total 4 - 7.47
Lancaster
Avista originally acquired output rights to the Lancaster CCCT, located in Rathdrum,
Idaho, after the sale of Avista Energy in 2007. Lancaster directly interconnects with the
Avista transmission system at the BPA Lancaster substation. Under the contract, Avista
pays a monthly capacity payment for the sole right to dispatch the plant through
December 31 , 2041. In addition, Avista pays an operational charge and arranges for all
fuel needs of the plant.
Palouse Wind
Avista signed a 30-year power purchase agreement (PPA) in 2011 with Palouse Wind for
the entire output of the 105 MW project starting in December 2012. The project directly
connects to Avista's transmission system between Rosalia and Oaksdale, Washington in
Whitman County. Avista has an annual right to purchase the Palouse project per the
contract.
Rd«Iesnake Flat Wind
Rattlesnake Flat Wind located east of Lind, Washington in Adams County was selected
in Avista's 2018 RFP as a 20-year PPA. It is 160.5 MW (but output is limited to 144 MW
due to its interconnection agreement). The expected net annual output of 469,000 MWh
(53.5 aMW). The project began operations in December 2020.
Clearwater Wind L__
Clearwater Wind III located in Rosebud and Garfield Counties in eastern Montana was
selected in the 2022 all-source RFP as a 30-year PPA. It is 97.5 MW and will begin
operation in September 2024 with an estimated annual generation of 367,000 MWh.
Adams-Nielson Solar
Avista signed a 20-year PPA for the Adams-Nielson solar project in 2017. The 80,000
panel, single axis, solar facility can deliver 19.2 MW of alternating current (AC) power and
48 This size is a little over 254 kW solar and the battery is greater than 1 MW but is limited to 1 MW output
by the inverter/interconnection.
49 This PPA was signed after the IRP analysis and therefore was not included in the IRP analysis.
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entered service in December 2018. The project is located north of Lind, Washington in
Adams County. The project provides energy for Avista's Solar Select program allowing
commercial customers to voluntarily purchase solar energy through 2026. Through
Washington state tax incentives participating customers do not pay additional costs for
the clean energy attributes from the project.
Sower Purchase and Contract:
Avista has intermediate power purchase and sale contracts to optimize Avista's energy
position on behalf of customers, such as the Morgan Stanley contract. For resource
planning purposes, Avista does not assume contract sale extensions. Table 4.9 describes
Avista's other contractual rights and obligations.
Table 4.9: Other Contractual Rights and Obligations
Contract Type Fuel Source End Winter Summer Annual
Date Capacity Capacity
M&llllllllll ��� (MA (MW) MEN
Lancaster Purchase Natural Gas 2041 283.0 231.0 218.0
Palouse Purchase Wind 2042 5.3 5.3 36.2
Rattlesnake Flat Purchase Wind 2040 7.2 7.2 53.5
Clearwater Wind Purchase Wind 2056 29.7 19.2 42.0
Adams-Nielson Purchase Solar 2038 0.4 10.2 5.6
Morgan Stanley Sale QF Biomass 2026 -46.0 -46.0 -44.9
Total 1 279.E 1 226.9 1 310.4
Resource Environmental Requirements and Issues
Avista is subject to environmental regulation by federal, state, and local authorities. The
generation, transmission, distribution, service, and storage facilities we own or may need
to acquire or develop are subject to environmental laws, regulations and rules relating to
construction permitting, air emissions, water quality, fisheries, wildlife, endangered
species, avian interactions, wastewater and stormwater discharges, waste handling,
natural resource protection, historic and cultural resource protection, and other similar
activities. These laws and regulations require the Company to make substantial
investments in compliance activities and to acquire and comply with a wide variety of
environmental licenses, permits, approvals, and settlement agreements. These items are
enforceable by public officials and private individuals. Some of these regulations are
subject to ongoing interpretation, whether administratively or judicially, and are often in
the process of being modified. Avista conducts periodic reviews and audits of pertinent
facilities and operations to enhance compliance and to respond to or anticipate emerging
environmental issues. The Company's Board of Directors has established a committee to
oversee environmental issues and to assess and manage environmental risk.
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Avista monitors legislative and regulatory developments at different levels of government
for environmental issues, particularly those with the potential to impact the operation of
generating plants and other assets. The Company continues to be subject to increasingly
stringent or expanded application of environmental and related regulations from all levels
of government.
Environmental laws and regulations may restrict or impact Avista's business activities in
many ways, including, but not limited to, by:
• increasing the operating costs of generating plants and other assets,
• increasing the lead time and capital costs for the construction of new
generating plants and other assets,
• requiring modification of existing generating plants,
• requiring existing generating plant operations to be curtailed or shut
down,
• reducing the amount of energy available from generating plants,
• restricting the types of generating plants that can be built or contracted
with,
• requiring construction of specific types of generation plants at higher
cost, and
• increasing the costs of distributing, or limiting our ability to distribute,
electricity and/or natural gas.
Compliance with environmental laws and regulations could result in increases to capital
expenditures and operating expenses. The following sections describe applicable
environmental regulations in more detail.
Policies and Other Impacts Related to Climate Change
Legal and policy changes responding to concerns about climate change, and the potential
impacts of such changes, could have a significant effect on our business. Direct impacts
of climate changes include, without limitation, variations in the amount and timing of
energy demand throughout the year, variations in the level and timing of precipitation
throughout the year, as well as variations in temperature, and the resulting impact on the
availability of hydroelectric resources at times of peak demand as well as an increased
risk of wildfire. Indirect impacts include, without limitation, changes in laws and regulations
intended to mitigate the risk of, or alter, climate changes, including restrictions on the
operation of power generation resources and obligations
Clean Energy Transformation Act
In 2019, the Washington State Legislature passed the CETA, requiring Washington
utilities to eliminate the costs and benefits associated with coal-fired resources from their
retail electric sales by December 31, 2025. This requirement effectively prohibits sales of
energy produced by coal-fired generation to Washington retail customers after December
31, 2025. In addition, retail sales of electricity to Washington customers must be carbon-
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Chapter 4: Existing Supply Resources
neutral by January 1, 2030 and requires that each electric utility demonstrate compliance
with this standard by using electricity from renewable and other non-emitting resources
for 100% of the utility's Washington retail electric load over consecutive multi-year
compliance periods; provided, however, that through December 31, 2044 the utility may
satisfy up to 20% of this requirement with specified payments, credits and/or investments
in qualifying energy transformation projects.
As required under the CETA, in October 2021 Avista filed our first CEIP. Our CEIP is a
road map of specific actions we proposed to take over the first four years (2022-2025) to
show the progress being made toward clean energy goals and the equitable distribution
of benefits and burdens to all customers as established by the CETA.
In June 2022, our CEIP was approved by the Washington Utility and Transportation
Commission (UTC).
Some highlights of our approved plan include:
• Beginning in 2022, serve 40% of Washington retail customer demand
with renewable (or zero carbon) energy, then the target increases to
62.5% by the end of 2025.
• Energy efficiency targets to reduce Washington retail customer load
by approximately 2% over the next four years through incentives and
programs to lower energy use without impacting the customer.
• A set of 14 CBIs to ensure the equitable distribution of energy and
non-energy benefits and reduction of burden to all customers and
Named Communities.
• A NCIF that will invest up to $5 million annually in projects, programs
and initiatives that directly benefit customers residing in historically
disadvantaged and vulnerable communities.
While the CEIP represented our objectives when filed, it is subject to change in the future
as circumstances warrant including direct input from the UTC. We are required to file a
CEIP every four years.
Emissions Performance Standard
Washington applies a GHG emissions performance standard to electric generation
facilities used to serve retail loads, whether the facilities are located within Washington or
elsewhere. The emissions performance standard prevents utilities from constructing or
purchasing generation facilities or entering into power purchase agreements of five years
or longer duration to purchase energy produced by plants that have emission levels
higher than 925 pounds of GHG per MWh. The Washington State Department of
Commerce reviews the standard every five years. The most recent review was completed
in 2024 and a new rate of 875 pounds CO2e per MWh will be adopted in October 2024.
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Chapter 4: Existing Supply Resources
Clean Air Act (CAA1
The CAA creates numerous requirements for our thermal generating plants. Colstrip,
Kettle Falls, Coyote Springs 2, and Rathdrum CT all require CAA Title V operating
permits. Boulder Park, Northeast CT and other operations require minor source permits
or simple source registration permits. We have secured these permits and certify our
compliance with Title V permits on an annual basis. These requirements can change over
time as the CAA or applicable implementing regulations are amended and new permits
are issued. Avista actively monitors legislative, regulatory and other program
developments of the CAA that may impact our facilities.
Coal Ash Management/Disposal
In 2015, the EPA issued a final rule regarding coal combustion residuals (CCRs), also
termed coal combustion byproducts or coal ash. Colstrip produces CCRs. The CCR rule
has been the subject of ongoing litigation. In August 2018, U.S. Court of Appeals for the
D.C. Circuit struck down provisions of the rule. In December 2019, a proposed revision
to the rule was published in the Federal Register to address the D.C. Circuit's decision.
The rule includes technical requirements for CCR landfills and surface impoundments
under Subtitle D of the Resource Conservation and Recovery Act, the nation's primary
law for regulating solid waste. The Colstrip owners developed a multi-year compliance
plan to address the CCR requirements along with existing state obligations expressed
through the 2012 Administrative Order on Consent (AOC) with the Montana Department
of Environmental Quality (MDEQ). These requirements continue despite the 2018 federal
court ruling.
The AOC requires MDEQ to review Remedy and Closure plans for all parts of the Colstrip
plant through an ongoing public process. The AOC also requires the Colstrip owners to
provide financial assurance, primarily in the form of surety bonds, to secure each owner's
pro rata share of various anticipated closure and remediation obligations. Avista is
responsible for our share of two major areas: the Plant Site Area and the Effluent Holding
Pond Area. Generally, the plans include the removal of boron, chloride, and sulfate from
the groundwater, closure of the existing ash storage ponds, and installation of a new
water treatment system to convert the facility to a dry ash storage. Our share of the posted
surety bonds is $16.8 million. This amount is updated annually, with expected obligations
decreasing overtime as remediation activities are completed.
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Washington Climate Commitment Act
The CCA, and its implementing regulations, established a cap-and-invest program to
reduce GHG emissions and achieve the GHG limits previously established under
Washington State law. The final rules implement a cap on emissions, provide
mechanisms for the sale and tracking of tradable emissions allowances and establish
additional compliance and accountability measures. The state issues allowances
necessary to serve our Washington retail electric load; off-system wholesale sales may
result in additional obligation costs. The CCA also directly impacts on our Idaho electric
operations as it applies to wholesale power sales delivered to Washington or power
generated in Washington for Idaho customers. In May 2023, a "lesser-than" model was
approved for use in calculating the allowances needed for compliance allowing
nonemitting generation to offset wholesale sales, therefore reducing the number of
allowances required. Annually, the model and its resulting calculations must be certified
by an independent third party and submitted to the Washington Department of Ecology
(Ecology) for approval. If the independent third party or Ecology disagrees with the
approach or any of the calculations, it could result in a change to the number of
allowances needed for compliance and could result in changes to anticipated costs for
our electric operations. For Washington electric, we are allowed to defer any incremental
costs associated with the CCA in accordance with our regulatory accounting order;
however, in Idaho we are not allowed to pass any costs associated CCA compliance to
Idaho customers at this time.
EPA Regulations for Power Plants
On April 25, 2024, the EPA released a package of final regulations addressed to electric
generation facilities. These include:
• Greenhouse gas regulations for new natural gas-based turbines and
existing coal-based units, pursuant to section 111 of the CAA. This
rule finalizes (a) the repeal of the Affordable Clean Energy rule; (b)
guidelines for GHG emissions from existing fossil fuel-fired steam
generating electric generating units; and (c) revisions to existing
performance standards for new, reconstructed or heavily modified
fossil fuel-fired stationary combustion turbine electric generating units.
• Supplemental Effluent Limitations Guidelines and Standards for the
Steam Electric Power Generating Point Source Category (ELG Rule).
The ELG Rule applies to wastewater discharges from coal-based
generating units and establishes pollution control requirements. The
Rule builds upon the 2015 and 2020 ELG Rules. It includes a
subcategory of requirements for coal plants retiring or repowering by
the end of 2028 and provides additional compliance pathways for coal
plants retiring by the end of 2034.
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Chapter 4: Existing Supply Resources
• Updated Mercury and Air Tox Standards, pursuant to section 112 of
the Clean Air Act (MATS Rule). The MATS Rule sets emissions limits
for filterable particulate matter for coal-based generating units. The
Rule reduces those limits from the standards that were originally set
in 2012.
• Disposal of Coal Combustion Residuals from Electric Utilities —
Legacy CCR Surface Impoundments (CCR Rule). The CCR Rule
builds on 2015 regulations, the rule applies to active power plants
disposing coal combustion residuals in surface impoundments or
landfills, by regulating inactive surface impoundments at inactive
power plants and CCR management units at active and inactive power
plants.
Avista is in the process of analyzing each of these rules to assess the impact, if any, it
may have on existing generating units, including Colstrip and/or our natural gas-fired
generating units. At this time, there are no indication the implementation of these rules
would impact our agreement to transfer our Colstrip ownership to NorthWestern on
December 31 , 2025. The owners (including the operator) have assessed the CCR Rule
and believe there will not be a material change to the asset retirement obligation for
Colstrip.
Washington State Building Codes
In April 2022, the Washington State Building Code Council (SBCC) approved a revised
energy code requiring most new commercial buildings and large multifamily buildings to
install all-electric space heating. An amendment to the code allows natural gas to
supplement electric heat pumps. In addition, in November 2022, the SBCC approved new
building and energy codes for residential housing, requiring new residential buildings in
Washington to use electricity as the primary heat source.
Both the commercial and residential building and energy codes were the subject of legal
challenges in both Washington State Superior Court (the State Action) and in the Federal
District Court for the Eastern District of Washington (the Federal Action). In the Federal
Action, (Avista was a party), the plaintiffs challenged the amendments on the grounds
that they were preempted by the federal Energy Policy and Conservation Act (EPCA),
citing the Ninth Circuit's decision in California Restaurant Association v. Berkeley (the
Berkeley Decision), which involved similar restrictions on the use of natural gas in new
construction in Berkeley, California.
In May 2023, the SBCC voted to delay the effective date of the code amendments and
commenced an emergency rulemaking process to evaluate additional amendments to the
code considering the Berkeley Decision. As a result of this action, in July 2023, the
Federal District Court declined to issue a preliminary injunction to prevent the
amendments from taking effect. The plaintiffs in the Federal Action subsequently
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Chapter 4: Existing Supply Resources
dismissed the action, without prejudice to their ability to refile after the SBCC rulemaking
process is complete.
The SBCC has since voted to approve revised residential and commercial energy
regulations to continue to require new residential and commercial buildings in Washington
to use electricity as the primary heat source. Considering this action, the plaintiffs in the
State Action amended their complaint to challenge the new regulations. The State Action
remains pending.
In May 2024, Avista, along with Cascade Natural Gas Corporation, Northwest Natural
Gas Company, and a coalition of homebuilders, heating unit dealers and other parties,
filed a lawsuit challenging the approved building codes on the grounds that they are
preempted by EPCA. The lawsuit was filed in the United States District Court for the
Western District of Washington. This lawsuit remains pending.
On November 5t", 2024 Initiative 2066 was passed by voters, this measure would repeal
or prohibit certain laws and regulations that discourage natural gas use, and/or promote
electrification, and require certain utilities and local governments to provide natural gas
to eligible customers. Given this initiative was passed after the IRP was prepared its
impact is not included in this plan. Avista believes the impacts is a minimal change in the
load forecast down as customers may decide to select natural gas during new
construction.
Particulate Matter (PM)
Particulate Matter (PM) is the term used for a mixture of solid particles and liquid droplets
found in the air. Some particles, such as dust, dirt, soot, or smoke, are large or dark
enough to see with the naked eye. Others are so small they are only detectable with an
electron microscope. Particle pollution includes:
• PMio: inhalable particles, with diameters that are generally 10
micrometers and smaller; and
• PM2.5: fine inhalable particles, with diameters generally 2.5
micrometers and smaller.
There are different standards for PM10 and PM2.5. Limiting the maximum amount of PM
to be present in outdoor air protects human health and the environment. The CAA
requires EPA to set National Ambient Air Quality Standards (NAAQS) for PM, as one of
the six criteria pollutants considered harmful to public health and the environment. The
law also requires periodic EPA reviews of the standards to ensure that they provide
adequate health and environmental protection and to update standards as necessary.
Avista owns and/or has operational control of the following generating facilities that
produce PM: Boulder Park, Colstrip, Coyote Springs 2, Kettle Falls CT, Lancaster,
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Chapter 4: Existing Supply Resources
Northeast and Rathdrum. Table 4.10 below shows each of the plants, status of the
surrounding area with NAAQS for PM2.5 and PMio, operating permit, and PM pollution
controls.
Appropriate agencies issue air quality operating permits. These operating permits require
annual compliance certifications and renewal every five years to incorporate any new
standards including any updated NAAQS status.
Fable 4.10: Avista Owned and Controlled PM Emissions
OperatingThermal PM2.5 PM10 Air Generating . . • NAAQS Permit
Boulder Park Attainment Maintenance Minor Source Pipeline Natural Gas
Colstrip Attainment Non- Major Source Fluidized Bed Wet Scrubber
Attainment Title V OP
Coyote Springs Attainment Attainment Major Source Pipeline Natural Gas, Air
2 Title V OP filters
Kettle Falls Attainment Attainment Major Source Multi-clone collector,
Title V OP Electrostatic Precipitator
Lancaster Attainment Attainment Major Source Pipeline Natural Gas, Air
Title V OP filters
Northeast Attainment Maintenance Minor Source Pipeline Natural Gas, Air
filters
Rathdrum Attainment Attainment Major Source Pipeline Natural Gas, Air
Title V OP filters
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Chapter 5: Resource Need Assessment
5. Resource Need Assessment
Avista plans its resource portfolio to meet multiple long-term objectives including serving
peak loads, providing operational and planning reserves, meeting monthly energy needs,
and meeting Washington's clean energy goals, as well as other applicable policies. This
chapter presents the long-term load and resource position through 2045 to determine
Avista's projected resource requirements. Notwithstanding future resource changes,
there are several fundamental changes to Avista's Loads & Resources (L&R) since the
2023 IRP, including the following developments:
• A 30-year Power Purchase Agreement (PPA) (97.5 MW) with
Clearwater Wind online in September 2024.
• Stimson Lumber co-gen (5.8 MW), a Qualifying Facility (QF) located
in Plummer, Idaho closed in 2024.
• A new Washington industrial customer increased load by 34.3 aMW
beginning in August 2024.
• Three Columbia Basin Hydro projects begin in 2025 totaling 105.8 MW
of capacity.
• A 5% slice (87.5 MW) of the Chelan PUD PPA comes online in 2026.
Section Highlights
• Avista's Planning Reserve Margin (PRM) requirement is 24% in the winter
and 16% in the summer.
• Avista's first long-term capacity and energy resource deficiency begins in
January 2030.
• The Western Resource Adequacy Program's (WRAP) qualifying capacity
credits (QCC) are used for Avista's resource capacity position.
• Under normal weather conditions, Avista has sufficient clean energy
resources to meet its projected Washington's Clean Energy
Transformation Act (CETA) targets through 2034.
Capacity Requirements
Avista must plan for its resource portfolio to have the capacity to reliably meet system
demand at any given time. Significant uncertainty is inherent in this exercise due to
situations when load exceeds the forecast and/or resource output falls below expectations
due to adverse weather, forced outages, poor water conditions, variability in wind/ solar
output, or other unplanned events. Under the PRM requirements, utilities are obligated to
carry more generating capacity to address uncertainty and meet forecasted peak
demand.
On average, reserve margins increase customer rates as compared to resource portfolios
without reserve margins due to the extra cost of carrying rarely used generating capacity.
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Chapter 5: Resource Need Assessment
Traditionally, reserve resources have the physical capability to generate electricity, but
most have higher operating costs, thus limiting revenue and dispatch. A balance must be
achieved between carrying enough capacity to address potential events and the cost of
carrying the unused capacity.
Prior to the development of the WRAP, Northwest electricity providers were operating
without an industry-standard reserve margin level, as it is difficult to enforce
standardization across systems with varying resource mixes, system sizes, and
transmission interconnections. Although the North American Electric Reliability Council
(NERC) defines reserve margins at 15% for predominately thermal systems and 10% for
predominately hydroelectric systems, it does not provide an estimate for energy-limited
hydroelectric systems such as Avista's. The WRAP is still in a non-binding trial phase, so
Avista cannot reliably count on other utilities meeting their reserve margin requirements.
In IRPs prior to 2023, a PRM of 16% in the winter months and 7% in the summer months
plus operating reserves and regulation requirements resulted in a total reserve margin of
24.6% in the winter months and 15.6% in the summer months. Those margins were
derived from a study of resources and loads using 1,000 simulations of varying weather
for loads, thermal generation capability, forced outage or derates on generation, water
conditions for hydroelectric plants, and wind generation. The reserve margins ensure
Avista's system can meet all expected load in 95% of the simulations, or a 5% Loss of
Load Probability (LOLP).
To align its PRM methodology with the WRAP, the 2023 IRP used a 22% PRM in the
winter and a 13% PRM in the summer along with reducing resource capabilities to
account for outages and other derates by using the WRAP's QCC methodology. Avista
did not conduct any additional reliability analysis to validate the PRM would result in a 5%
LOLP due to the fact the region would be resource sufficient if all utilities met their WRAP
targets.
For the 2025 IRP, Avista conducted a reliability analysis to ensure the planning margin
creates an adequate system. Avista developed a LOLP study using Avista Resource
Adequacy Model (ARAM)50 to determine the ability of its system to meet load and
reserves each hour when subjected to 1,000 iterations with differing combinations of
water years, load, temperature, maintenance, forced outages, and VER production. The
model optimizes storage hydro projects within parameters of each project's FERC
license. This allows a realistic representation of the hydro system's capability to meet
load. This study utilized the current expected portfolio of load and resources in 2030 along
with the ability to purchase up to 330 MW from the market. Avista conducted multiple
studies adding capacity resources (i.e., natural gas turbine) to achieve a 5% LOLP (see
Table 5.1). The result of this analysis indicates a need of 50 MW by 2030 and infers a
so ARAM is an Excel-based model using VBA code and Excel's linear optimization add-in What's Best!
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Chapter 5: Resource Need Assessment
24% planning margin in the winter months to be resource adequate. The summer months
reflect minimal resource adequacy shortfalls due to existing resource flexibility and the
addition of the Columbia Basin Hydro projects. To ensure enough resource adequacy,
Avista is using a summer planning margin based on its single largest contingency
resource as a percentage of load. The largest single contingency is Coyote Springs 2 at
16% of summer peak load. The new study identifies a slightly larger PRM than the 2023
IRP value for winter months. Much of this change is due to accounting for reserves Avista
must hold to participate in the Western Energy Imbalance Market (EIM) due to its
renewable energy fleet. In addition to LOLP there are 5 other metrics used to evaluate
reliability. The following defines how each is calculated51:
• LOLP — Loss of Load Probability: Calculated by counting the number
of iterations where there is unserved load or unmet reserves and
dividing by the total number of iterations. This metric can be used to
determine the probability or likelihood of events due to insufficient
capacity.
• LOLE — Loss of Load Expectation: Calculated by counting the days
where there is unserved load or unmet reserves and dividing by the
total number of iterations. The majority of entities conducting LOLE
studies primarily use it to establish resource adequacy criteria.
Industry standard is 0.1 days per year LOLE.
• LOLEV — Loss of Load Expected Events: Calculated by counting the
number of consecutive blocks of unserved load or unmet reserves and
dividing by the number of iterations. The LOLEV metric is useful in
systems that are concerned with the frequency of events, regardless
of duration or magnitude.
• LOLH — Loss of Load Hours: Calculated by summing the number of
hours with unserved load or unmet reserves and dividing by the total
number of iterations. The LOLH metric is computed by a large number
of entities in North America. However, only one entity uses this metric
as a reliability criterion, with their criterion set a 2.4 hours per year.
• EUE — Expected Unserved Energy: Calculated by summing all the
unserved MWhs over the study period and dividing by the number of
iterations. Two versions are presented, one with unmet reserves and
one without. EUE is useful in estimating the size of the loss of load
events so planners can estimate the cost and impact of the loss of
load events.
51 Reliability metric information from the NERC, Probabilistic Adequacy and Measures Report, July 2018
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Chapter 5: Resource Need Assessment
Table 5.1: 2030 Resource Adeuudcy Stuay
030 2030 with 30 2030 with 50
lu Resources Resources
New
Resources
LOLP 6.9% 5.5% 5.1%
LOLE 0.23 0.16 0.10
LOLH 2.59 1.92 1.56
LOLEV 0.50 0.40 0.33
EUE with reserves 488 338 1 268
EUE (without reserves) 1 468 325 256
Western Resource Adequacy Program
In response to the growing penetration of renewable variable energy resources and
retirements of thermal generation in the West, the Western Power Pool (WPP) initiated
an effort in 2019 to understand capacity issues in the region and identify potential
solutions. The product of these efforts resulted in the WRAP. The WRAP's purpose is to
leverage the diversity of loads and generation throughout the WECC so individual entities
do not need to carry the full burden of supplying adequate capacity for their systems. The
FERC filing to establish a tariff for the WRAP describes the program as follows:
The WRAP leverages the existing bilateral market structure in the West to
develop a resource adequacy construct with two distinct aspects: (1) a
Forward Showing Program through which WPP forecasts Participants' peak
load and establishes a Planning Reserve Margin ("PRM') based on a
probabilistic analysis to satisfy a loss of load expectation ("LOLE) of not more
than one event-day in ten years, and Participants demonstrate in advance that
they have sufficient qualified capacity resources (and supporting transmission)
to serve their peak load and share of the PRM; and (2) a real-time Operations
Program through which Participants with excess capacity, based on near-term
conditions, are requested to "holdback" capacity during critical periods for
potential use by Participants who lack sufficient resources to serve their load
in real-time.
The WRAP is a resource adequacy planning and compliance framework where program
participants voluntarily join. However, once committed, utilities are obligated to comply
with requirements or be fined for non-compliance. To demonstrate compliance with the
WRAP's Forward Showing Program (FSP), a participant must demonstrate its QCCs for
resources and contracts are equal to or greater than peak demand, plus the assigned
monthly PRM and less demand response programs. Load, hydro and renewable output,
thermal resource capacity, forced outage data, and planned outage schedules are
provided to the program operator who then provides QCC values for specific resources
and an assigned peak load. Metrics for the winter and summer FSP for 2024 have been
established and Avista has adequate resources to meet the requirement. The WRAP is
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Chapter 5: Resource Need Assessment
continually updating its business practices to reflect best practices and updated data from
historical operations.
Maintenance Planning
Avista generating units require periodic maintenance over the planning horizon. The
challenge is forecasting when and what units will be unavailable due to future
maintenance needs. Avista includes an adjustment to its peak planning forecast to
account for unit maintenance using a combination of historical outages and a forecast of
routine maintenance schedules. Avista's forecast shown in Figure 5.1 is a total of the
maintenance from all plants on average. This amount is in additional adjustment above
the PRM Avista includes when calculating its capacity position. Most maintenance occurs
in the spring and fall months when loads are lower, while hydro maintenance is at higher
levels in the spring allowing thermal units to go on maintenance due to extra generation
supply.
Figure 5.1: Maintenance Adjustment for Capacity Planning
400
350 345
300
N
250 227
cC
200
160
150
cC
118
Q100 93 81
54 50
50 28 33 30 38
_. .1 In
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Avista's Capacity Need Assessment
Based on Avista's analysis of resource adequacy, Avista is temporarily short capacity in
2026 until a sale contract expires. After this contact expires, Avista is in a near balanced
position until 2030. In 2030, between load growth, retirement of the Northeast CT, and
expiration of a long-term PPA the utility will be deficient on a permanent basis until new
resources are acquired. Figure 5.2 illustrates the winter capacity need by comparing the
controlled resources in the blue bars compared to the peak load and PRM in the black
line. Avista's summer position is similar to winter as the first permanent resource deficit
also begins in 2030 and is shown in Figure 5.3.
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Chapter 5: Resource Need Assessment
Figure 5.2: Winter One-Hour Peak Capacity Load and Resources Balance
3,000
2,500
N 2,000
1,500
. 1
d
1,000
i Existing/Committed Resources
500 Planning Requirement w/PRM
—Load Forecast(1 in 2 Event)
0 —
c0 r1- 00 M O � N CO U) (0 r-- 00 O O N CO U)
N N N N (M co co M M M M M M co It It It It It qt
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Figure 5.3: Summer One-Hour Peak Capacity Load and Resources Balance
3,000
2,500
N 2,000
1,500
a�
m
� 1,000
Existing/Committed Resources
500 Planning Requirement w/PRM
—Load Forecast(1 in 2 Event)
0
(0 r,- 00 M O — N CO U-) O rl- 00 M O N CO u7
N N N N co co co M M M co co M M �t q�t �t It It
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
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Chapter 5: Resource Need Assessment
Energy Requirements
In contrast to peak planning, energy planning determines the need based on customer
demand with a time duration element. Avista evaluates energy planning on a monthly
target basis for meeting customer demand, renewable targets, and evaluating generation
risks. In the transition to renewable energy resources with differing energy delivery time
periods, Avista is now using monthly energy requirements. This ensures Avista does not
acquire too much energy in certain periods such as spring and not enough in higher
expected load months such as August or January. This monthly planning creates
significant generation length in spring and fall months as renewable resources typically
do not only supply energy in the months needed.
The monthly energy analysis requires additional steps beyond capacity planning to
account for what may happen to a resource's operations. Evaluation of monthly
generation is specific to the resource in question, e.g., the factors impacting hydro
generation are different than the factors impacting thermal generation. This section
compares monthly generation and monthly demand to determine deficit and surplus
conditions for the 2026 to 2045 period. A discussion of monthly demand is provided in
Chapter 3. Table 5.2 details how monthly generation for each resource type is evaluated.
-ble 5.2: Monthly Entw.uy Evaluation Methodo,wu,,uQ
MethodologyResource Type jFvaluation
Biomass Unit capacity reduced by a percentage according to planned and forced
outage rates.
Natural Gas Unit capacity adjusted for monthly ambient average temperature and reduced
Combined Cycle by a percentage according to planned and forced outage rates and any
runtime limitations imposed by operating permits.
Natural Gas Unit capacity reduced by a percentage according to planned and forced
Peaker outage rates and any runtime limitations imposed by operating permits.
Wind Five year monthly average output if available, or average output estimates
provided by facility operator.
Solar Five year monthly average output if available, or average output estimates
provided by facility operator.
Hydro Monthly median generation of the previous 30 years. Future years include
both historical and forecasted monthly generation.
Energy Risk/Contingency Evaluatioi
In addition, hydro generation and load both include the predicted impact of forecasted
temperature changes and risk evaluation includes variability in all renewables rather than
just hydro. Energy planning is based on average conditions. The load forecast utilizes 20-
year average weather conditions, while the hydro generation estimates are based on the
median over a 30-year period. There is a risk the load can be larger and/or hydro
generation can be lower than forecasted. Additionally, in the last decade, Avista has
added wind and solar generation to its portfolio — both having variable output period-to-
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Chapter 5: Resource Need Assessment
period. Avista adds a contingency adjustment to the load and resource balance evaluation
to address this risk.
Avista develops a monthly estimate of load and generation for each hydro, wind, and
solar facility for weather conditions for each month between 1948 and 2019 for the
contingency adjustment. Total generation is then subtracted from load for each month
creating a monthly energy position of the at-risk components of the portfolio. A distribution
of the variability is created with this historically based data set, and Avista uses the 95t"
percentile of the monthly values as compared to the expected position. The result
represents the energy necessary to meet the risk of above average loads occurring during
periods of low hydro, wind, and solar production. The result of this analysis is shown in
Figure 5.4. These energy quantities are added to the load forecast to account for the
variability.
Figure 5.4: Energy Contingency Assumption
350
320
305
300
254
w 250 228
218 212
1° 200 184
167 171
150
118 119 127
a'
100
50
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Net Energy Position
Avista's net energy position is determined by summing all generation rights from Avista's
facilities and PPAs and subtracting obligations including forecasted monthly load,
contracted sales, and accounting for the energy contingency. Table 5.3 presents net
monthly energy positions for selected years.
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Chapter 5: Resource Need Assessment
Table 5.3: Net Energy Position
2030 - 2040
January -26 -69 -168 -866
February 22 46 -13 -733
March 170 184 81 -578
April 345 328 216 -310
May 706 692 581 101
June 518 501 355 -143
July 173 142 -11 -672
August 74 41 -96 -725
September 198 191 83 -533
October 170 164 55 -565
November 59 27 -85 -744
December 16 1 -2 1 -147 1 -836
Forecasted Temperature & Precipitation Analysis
The 2023 IRP first included future climate forecasts for estimating load and hydro
generation and the 2025 IRP uses the same forecasts. The forecast is based on the
climate analysis developed for the Columbia River Basin by the River Management Joint
Operating Committee (RMJOC) comprised of the Bonneville Power Administration (BPA),
United States Army Corps of Engineers, and United States Bureau of Reclamation. The
RMJOC, in conjunction with the University of Washington and Oregon State University,
completed two studies (2018 and 2020) for the 2020-2100 study period utilizing
downscaled global climate models (GCMs), hydrology and reservoir operation models to
predict monthly river flows for locations throughout the Columbia River Basin, including
all of Avista's hydroelectric facility locations. The RMJOC has not conducted any new
analysis, nor has any other organization conducted similar analysis to replace the RMJOC
dataset. Therefore the 2023 IRP dataset is being used in the 2025 IRP.
There is significant uncertainty in projecting future temperatures and precipitation and the
subsequent impact on streamflow and reservoir operations. The RMJOC used an
ensemble approach to capture a range of potential outcomes. The approach used unique
combinations of two representative concentration pathways (RCPs), ten GCMs, three
downscaling techniques and four hydrology models. In total there were 172 unique model
combinations resulting in 172 streamflow datasets for each location. The streamflow data
was then used in reservoir operation models generating monthly flows under current
operating parameters for each of the Columbia Basin hydroelectric facilities. Flow data
allows for an estimate of generation at each of the facilities.
Given the sheer volume of data, a method to select a representative set from the 172
modeling combinations was needed. Fortunately, BPA conducted this exercise and
selected a subset of modeling combinations representing a sufficient cross section of
outcomes to calculate expected generation. The subset represents 19 modeling
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Chapter 5: Resource Need Assessment
combinations for both RCP 4.5 and RCP 8.5. RCPs represent different greenhouse gas
(GHG) emission scenarios varying from no future GHG reductions to significant GHG
reductions. The Intergovernmental Panel on Climate Change (IPCC) describes the
following scenarios:
• RCP 2.6 - stringent GHG mitigation scenario
• RCP 4.5 & RCP 6.0 - intermediate GHG scenarios
• RCP 8.5 - very high GHG scenarios.
Table 5.4 provides a comparison of the temperature increases projected under the
various scenarios.
Table 5.4: Comparison of T----rature Increas- by Rrp
- . 0. 00
-&6 mean jliWely range mean Likely r�
Global Mean RCP 2.6 1.0 0.4 to 1.6 1.0 0.3 to 1.7
Surface RCP 4.5 1.4 0.9 to 2.0 1.8 1.1 to 2.6
Temperature RCP 6.0 1.3 0.8 to 1.8 2.2 1.4 to 3.1
Change (°C) RCP 8.5 2.0 1.4 to 2.6 3.7 2.6 to 4.8
The RCP 4.5 and RCP 6.0 scenarios are similar during the current IRP planning horizon.
Avista selected modeling results based on the RCP 4.5 for winter months and RCP 8.5
for summer months for load forecasting and RCP 4.5 for hydro forecasting. Avista chose
this approach given:
• RCP 8.5 is at the high end of potential future GHG emissions,
• there are significant worldwide efforts to mitigate GHG emissions,
• the intermediate scenarios are similar during the IRP planning horizon,
• using RCP 8.5 temperatures for planning protects against higher
summer temperatures,
• during time periods where both modeled and actual values are
available, the RCP 4.5 and 8.5 have overestimated winter
temperatures on average (except for January) but have
underestimated summer temperatures for the Spokane region as
shown in Figure 5.5.
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Chapter 5: Resource Need Assessment
Figure 5.5: Monthly Average Temperature RCP 8.5, RCP 4.5, dMA Actual 2020-24
80
-RCP 4.5 ■RCP 8.5 •Actual ' •
70
60
LL •
N
50CL
•
m •
C
aa) 40 •
F-
•
30 • •
•
20
L
m m P s s
i m �' E E E
u- fl O o a�i
U) z
Hydro Forecasting
Utilizing a regression modeling relating flow to generation, Avista converted each of the
19 BPA-selected monthly river flow modeling combinations for Avista facilities. The
median of the 19 modeling combinations was selected to represent generation at each
facility for each specific month and year.
Avista has contracts to receive a specified portion of generation from five facilities on the
Columbia River—Wells, Rock Island, Rocky Reach, Wanapum, and Priest Rapids—these
are owned and operated by Douglas PUD, Chelan PUD, and Grant PUD. BPA analyzed
generation at each of these facilities for each of the RCP 4.5 scenarios. As with the Avista
facilities, the median of the 19 modeling combinations was selected to represent
generation at each facility for each month and year over the planning horizon.
Prior IRPs used monthly hydro generation by estimating generation occurring under
current operating parameters for each water year from 1929 to 2008 (80-year hydro
record) and taking the median value for each month for each facility. In this analysis,
Avista changed the methodology to use the median monthly value of the previous 30
years, e.g., 2022 estimated generation is the median of generation values from 1992-
2021. Future years incorporate a mix of historical generation data and forecasted
generation data.
Table 5.5 and Figure 5.6 present the differences between the 80-year hydro record and
the recent 30-year record resulting from the RCP 4.5 analysis. Annual hydro generation
is similar between the 80-year hydro record and recent 30-year record, as it is projected
warming temperatures will increase annual hydro generation. On a monthly basis there
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Chapter 5: Resource Need Assessment
is an increase in hydro generation during the winter and early spring months, and a
decrease in the summer months. This is consistent with regional forecasts predicting an
overall increase in annual precipitation with less snow fall and an earlier snowpack melt.
Table 5.5: Hydro G_____-- . Forecast Comparisoi, kaivivv)
80-Year Hydro Recent 30-Year RCP 4.5
IL (1929-2008) (1992-2021) (2019-2049)
Mean 598 595 645
Median 597 585 636
loth Percentile 424 437 447
90' Percentile 776 756 858
Standard Deviation 1 142 1 137 1 169
rigure 5.6: Comparison of Recent 30-Year, and RCP 4.5 Generation
200
150 Difference between 80-Year Hydro and:
■Recent 30 Year
100 ■RCP 4.5 2019-2049
50 79 68
7 . CO 4112
0
-14-18 -1 -15 -2
-50
-100
-150
:3 Q E P E E
ti Q 0 o 0
N Z 0
In addition to impacting hydro generation, warming temperatures will also impact demand.
Specifically, where the forecast assumes less heating required in the winter and more
cooling required during the summer. To assess the load impacts, the temperature data
sets used as the basis of the streamflow data sets were used in the load forecast and are
described in Chapter 3.
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Chapter 5: Resource Need Assessment
Washington State Renewable Portfolio Standard
Washington's Energy Independence Act (EIA) promotes the development of regional
renewable energy by requiring utilities with more than 25,000 customers to source 15%
of their energy from qualified renewables by 2020. Utilities must seek to acquire all cost-
effective energy efficiency. In 2011, Avista signed a 30-year PPA for Palouse Wind to
help meet the EIA goal. In 2012, an EIA amendment allowed Avista's Kettle Falls biomass
generation to qualify for the goals beginning in 2016. More recently, Avista acquired the
Rattlesnake Flat Wind, Adams Nielson Solar,52 and Clearwater Wind III adding to qualified
generation.
Table 5.6 shows the forecasted Renewable Energy Credits (RECs)53 Avista needs to
meet the ETA's renewable requirements and the qualifying resources within Avista's
current generation portfolio. This table does not reflect the EIA REC banking provision
allowing a single year of retainment of RECs. Avista uses this banking flexibility as needed
to manage variation in renewable generation.
I duce J.o. vvdb11111Yw11 QLdLe rziiA %,u.opliance Position Prior to REC Banking
(aMW)
030
Two-Year Rolling Average WA Retail Sales Estimate 726.8 739.7 739.7
Renewable Goal 109.0 111.0 110.9
Incremental Hydro 18.0 18.0 18.0
Other Available RECs
Palouse Wind with Apprentice Credits 46.0 46.0 46.0
Kettle Falls 36.1 36.1 46.8
Rattlesnake Flat with Apprentice Credits 60.6 60.6 60.6
Adams Neilson Solar - - 5.5
Boulder Community Solar 0.1 0.1 0.1
Rathdrum Solar 0.0002 0.0002 0.0002
Clearwater Wind 1 41.9 1 41.9 1 41.9
Excess Renewable Excess before rollover RECs 1 93.7 1 91.7 1 108.0
Washington State's Clean Energy Transformation Act
CETA requires Washington State electric utilities to serve 100% of Washington retail load
with renewable and non-emitting electric generation by 2045. Beginning in 2030, at least
80% of generation must be from renewable and non-emitting electric generation and up
52 Adams Nielson can be used for the EIA after the voluntary Solar Select program ends in 2028.
53 These RECs are qualifying RECs within Avista's system. For state compliance purposes, Avista may
transfer RECs from one state's allocation shares to another at market prices. Avista may also sell excess
RECs to reduce customer rates.
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Chapter 5: Resource Need Assessment
to 20% can be met with alternative compliance options including alternative compliance
payments, unbundled RECs, or investing in energy transformation projects. CETA
requires the Washington Utilities & Transportation Commission (UTC) to adopt rules for
implementation. In this IRP, the 20% alternative compliance component is assumed to
decrease to zero in 5% increments by 2045.
A remaining unknown consideration for compliance with CETA relates to the UTC's
determination of compliance with RCW 19.405.030(1)(a) defining "use" of clean energy.
The UTC has an ongoing rulemaking proceeding54 to determine the interpretation of"use"
in CETA and recent submitted draft rules available for comment. While CETA rulemaking
is still in development, Avista's 2021 Clean Energy Implementation Plan (CEIP) includes
compliance targets approved by the UTC for 2022-2025. Avista's 2021 CEIP was
conditionally approved in Order 01 of Docket UE-210628. The 2021 CEIP does not
include a commitment or approved targets for the 2026-2029 or 2030-2044 periods.
Between 2030 and 2044, all generation used to serve Washington electric retail load must
be greenhouse gas neutral, while up to 20% can be met through alternative compliance
options. Interim targets to meet the 2045 standard will be determined in a future CEIP
after final "use" rules have been adopted. Table 5.7 presents the approved interim targets
for 2022-2025 and preliminary targets through 2045.
Table 5.7: CETA Compliance Target Assumptions
. . Compliance Alternative
Target Compliance
2022 40.0% 0%
2023 47.5% 0%
2024 55.0% 0%
2025 62.5% 0%
2026 66.0% 0%
2027 69.5% 0%
2028 73.0% 0%
2029 76.5% 0%
2030 — 2033 80.0% 20%
2034 — 2037 85.0% 15%
2038 — 2041 90.0% 10%
2041 — 2044 1 95.0% 1 5%
2045 1 100.0% 1 0%
Note: A commitment has been made in the
CEIP for values in bold.
Multijurisdictional utilities face unique challenges with CETA compliance as resource
costs and benefits are allocated to each state using a ratio derived from load. The IRP
proposes resource selections based on each state's policies, however, when resources
54 Docket UE-210183.
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Chapter 5: Resource Need Assessment
are added to the system, the other state still receives its share of the costs and benefits.
Until a new allocation methodology is approved by each Commission, Avista makes the
following assumptions:
• Qualifying clean energy is determined by procurement and delivery of
energy to Avista's system.
• The clean energy goal is applied to retail sales less in-state PURPA
generation constructed prior to 2019 plus voluntary customer
programs such as Solar Select.
• Voluntary customer REC programs, such as Avista's My Clean
EnergyTM program, do not qualify toward the CETA standard.
• Compliance generation includes:
• Washington's share of legacy hydro generation (defined the facility is
operating or contracted with deliveries before 2022).
• All wind, solar, and biomass generation in Avista's portfolio. Nonpower
attributes or RECs associated with Idaho's portion of generation,
according to the established production transmission (PT) ratio, will be
purchased by Washington at market rates if used for compliance in
Washington.
• Newly acquired (post 2019) or contracted non-emitting generation
including hydro, wind, solar, or biomass can be used for compliance
using the same methodology as existing Avista-owned non-
hydroelectric generation55 when purchasing the nonpower attributes
from Idaho to Washington.
• Avista is not planning to use Idaho's share of legacy hydroelectric to
meet Washington's clean energy goals prior to 2030, however actual
compliance may include them due to variability in clean resource
availability (e.g., for a low water year). Avista may include these hydro
resources toward alternative compliance if it is economic to acquire
the renewable energy attributes.
• Avista uses total monthly generation to estimate if clean energy counts
toward the compliance target or alternative compliance. If
Washington's clean energy generation total is greater than its "net
retail load," excess generation is applied toward alternative
compliance. However, all generation below "net retail load" counts as
compliant clean energy to meet the 4-year CEIP targets such as 80%
by 2030.
A forecast based on a 30-year moving median of hydro conditions, average solar and
wind generation, and the current load forecast is presented in Figure 5.7. The analysis
demonstrates Avista has enough qualifying resources to meet primary compliance targets
through 2033 using this methodology but will need additional energy for the 2034-2038
CEIP period. Depending on the outcome of the clean energy "use" rules, the shortfall
55 Such as Palouse Wind and Kettle Falls with historical precedence of transferring between states for EIA
compliance.
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Chapter 5: Resource Need Assessment
could change as well as actual production due to weather outside of average conditions.
For alternative compliance, between generation exceeding retail load and legacy hydro
energy from Idaho, Avista has enough qualifying energy to meet this requirement through
2044. (Alternative compliance is not required after 2045 by statute, but rather a goal of
serving 100% of demand with clean energy). The light blue bar in Figure 5.7 represents
the amount of energy transferable from Idaho for primary compliance. Avista's modeling
selects this energy only if new generation is more expensive.
Figure 5.7: Washington State CETA Compliance Position
1,200
1,000
1 1
800
as
600
d
Q
400
Primary Compliance Target �Alternative Compliance
Q 200 Allocated Primary Compliance Generation �Available Idaho Primary Compliance Transfers
Primary Compliance Shortfall �Allocated Alternative Compliance Generation
Available Alt. Idaho Hydro Generation — — Net Retail Sales
CO 00 O O N CO It Cn CO fl- 00 O O NCO LO
N N N N CO M co M M M CO M M M I V It It V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Reserves and Flexibility Assessment
Avista released a Request for Information (RFI) for a Variable Energy Resource (VER)
integration study in February 2022. Energy Strategies was selected to develop a
framework to quantify the incremental integration cost of a range of potential VER
penetration levels as informed by Avista's 2023 IRP Preferred Resource Strategy (PRS)
to serve Avista's projected load.
This VER integration study supports Avista's efforts toward carbon-neutrality goals and
providing reliable, lowest cost energy. A prior VER integration study was performed in
2007 and updated in 2014, but changes regarding resource capital costs, Avista's current
and projected resource mix, Avista's participation in the Western EIM, and state policies
requiring greater VER penetration, all warranted an updated study.
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Chapter 5: Resource Need Assessment
Phase
Integration cost is primarily driven by the need to hold higher levels of operating reserves
caused by the variability and uncertainty of VER production. Energy Strategies developed
data inputs for 12 VER scenarios for modeling in Avista's Decision Support System
(ADSS) production cost model. These 12 production profiles were based on likely
development locations informed from past generation proposals and utilized National
Renewable Energy Laboratory's (NREL) Wind Integration National Dataset (WIND) and
Solar Integration National Dataset (SIND) as well as the National Solar Radiation
Database (NSRDB) to compile site-specific proxy production and forecast profiles for
each VER site. Energy Strategies calculated reserve levels utilizing 2021 actual
operations with confidence intervals via statistical analysis based on seven historical
weather years. Energy Strategies also evaluated the impact of Western EIM on reserves
and determined the diversity savings benefit to be approximately 50%. The results of their
study are shown in Figure 5.8.
VER Integration Cost Estimates
Avista utilized its ADSS product cost model to study 12 VER scenarios (13 including the
existing resource scenario) to calculate integration costs as well as high and low
sensitivities. Energy Strategies' Phase 1 reserve amounts were adjusted for the diversity
benefit and used as constraints in the ADSS model. The resulting integration costs $/kW-
month and $/MWh for the scenarios and sensitivities are shown in Table 5.8.
Figure 5.8: Flexible Reserves Required by VER Future
VER Profile Operating Reserves
Around-the-Clock Average
Baseline +OMW Z t Dn_Reg
Wind +400 MW Up_Reg
Dn LF
Wind +800 MW Up_LF
Dn FcstErr
Wind +1500 MW Up_FcstErr
Wind +2500 MW
50/50 +400 MW
50/50 +800 MW
50/50 +1500 MW C
50/50 +2500 MW
Solar +400 MW
Solar +800 MW o�
Solar +1500 MW
Solar +2500 MW -
-600 —400 —200 0 200 400 600
MW
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Chapter 5: Resource Need Assessment
Table 5.8: VER Study Results
Integration Cost ($/kW-month) Integration Cost ($/MWh)
Base High MM Low Base MM High a_ Low d
Existing Portfolio 0.19 0.40 0.15 0.54 1.12 0.44
50/50 + 400 MW 0.16 0.34 0.09 0.56 1.19 0.32
50/50 + 800 MW 0.19 0.39 0.11 0.69 1.43 0.40
50/50 + 1,500 MW 0.17 0.33 0.10 0.70 1.41 0.43
50/50 + 2,500 MW 0.22 0.39 0.20 0.98 1.74 0.90
Solar + 400 MW 0.12 0.26 0.07 0.40 0.85 0.23
Solar + 800 MW 0.12 0.25 0.07 0.43 0.90 0.25
Solar + 1,500 MW 0.11 0.23 0.07 0.43 0.87 0.27
Solar + 2,500 MW 0.21 0.33 0.22 0.84 1.33 0.90
Wind + 400 MW 0.22 0.48 0.13 0.89 1.90 0.50
Wind + 800 MW 0.27 0.56 0.16 1.21 2.50 0.70
Wind + 1,500 MW 0.25 0.48 0.19 1.25 2.44 0.94
Wind + 2,500 MW 0.85 1.21 0.79 4.92 7.05 4.56
Phase II
Energy Strategies validated the integration costs resulting from the ADSS modeling. In
addition, a calculator for varying levels and combinations of VERs was created to aid in
estimating integration costs for resource planning and selection. This work was completed
by 2024.
Capacity Planning for Reserves and Flexibility
When Avista joined the Western EIM, it required the company to maintain flex ramp
reserves prior to the operating hour. Flex ramp reserve amounts are based upon historical
load, solar, and wind variations. As VERs are added to the system, if all other
assumptions remain constant, Avista will need to increase the amount of flexible ramp
resources it must carry. In addition to the flex ramp requirement, Avista must also carry
operating reserves in the event of a generator outage. Other reserves the utility must
maintain to handle generation is ramping hour-to-hour. Fortunately, for Avista, the hydro
system provides much of its reserve capability along with its natural gas peaking fleet.
When selecting the resource strategy, the model includes a requirement to carry enough
reserves to meet the flexibility requirements using either existing resources or new
resources. A summary of the flex ramp requirements assumed depending upon the new
resources acquired are shown in Figure 5.8 as used in the integration cost estimate. For
inclusion in the resource plan, Avista translated the finding from this study into an equation
to calculate flexibility based on the amount of load and resources as follows:
quation 5.1: Modeled Flex Ramp
Modeled Flex Ramp (MW) = 83.8 + Total Solar x 0.10 + Total Wind 0.12 + Load x 0.21
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Chapter 5: Resource Need Assessment
Natural Gas Pipeline Analysis
Avista transports fuel to its natural gas-fired generators using the Gas Transmission
Northwest (GTN) pipeline owned by TC Energy (formally TransCanada). The pipeline
runs between Alberta, Canada and the California/Oregon border at Malin, Oregon. Avista
holds 60,592 dekatherms per day of capacity from Alberta to Stanfield, Oregon and
controls another 26,388 dekatherms per day from Stanfield to Malin. Figure 5.9 below
illustrates Avista's firm natural gas pipeline rights. This figure includes the theoretical
capacity if the plants under Avista's control run at full capacity for the entire 24 hours in a
day on the system. The maximum burn by Avista is 148,342 dekatherms per day based
on the average of the top five historical natural gas burn days, as shown in Table 5.9.
Avista does not have firm transportation rights for the entirety of its natural gas generation
capacity but rather relies on short-term transportation contracts to meet needs above its
firm contractual rights. Adequate surplus transportation has historically been available
because the GTN pipeline was not fully subscribed. Natural gas producers have recently
purchased all remaining rights on the system to transport their supply south to take
advantage of higher prices in the U.S. compared to Canada. However, these suppliers
do not appear to have firm off-takers of their product, and therefore a lack of transportation
likely will not lead to a lack of fuel for Avista's natural gas plants, but this remains a risk.
Historically, when suppliers control the pipeline capacity, it has resulted in a pricing issue
rather than a supply issue. In extreme winter conditions or if pipeline capacity is lost (as
occurred in January 2024), the inability to control gas capacity could result in shutting off
gas generation. Avista has identified three solutions to address this issue; 1) install on-
site alternative fuel storage, i.e., fuel oil, 2) acquire or build new natural gas pipelines, or
3) develop regional Liquefied Natural Gas (LNG) storage. On-site fuel oil storage is
possible for smaller natural gas turbines with modifications and air permit modifications.
Either acquiring or building new natural gas pipelines is not a viable option. If Avista is
going to solve this fuel supply risk, an LNG facility should be constructed. This solution
could also alleviate pipeline delivery risk to the local gas delivery system.
Table 5.9: Top Five Historical Peak Day Natural Gas Usage (Dekatherms)
Date Boulder
Park Springs 2 Rights
1/18/2024 4,573 51,540 46,806 45,931 148,849 60,592
1/30/2023 4,571 51,567 48,206 44,441 148,785 60,592
1/17/2024 5,349 51,455 45,273 46,651 148,728 60,592
2/16/2024 5,451 50,530 46,611 45,404 147,996 60,592
1/16/2024 5,372 51,939 43,781 1 46,260 1 147,351 1 60,592
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Chapter 5: Resource Need Assessment
Figure 5.9: Avista Firm Natural Gas Pipemw RiyllLb
Pipeline Capacity
60,592 DThIDay Lancaster 49,000
Rathdrum 43,600
Boulder 5,400
98,000 DThIDay
Coyote Springs _
53,550 DThIDay '
Pipeline Capacity
26,388 DThIDay
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Chapter 6: Distributed Energy Resource Options
6. Distributed Energy Resource Options
Distributed Energy Resources (DERs) include energy efficiency, demand response,
existing resources, and new resource options such as customer sited solar and energy
storage. In WAC 480-100-605 DERs are defined as:
Distributed energy resource means a non-emitting electric generation or
renewable resource or program that reduces electric demand, manages the
level or timing of electricity consumption, or provides storage, electric
energy, capacity, or ancillary services to an electric utility and that is located
on the distribution system, any subsystem of the distribution system, or
behind the customer meter, including conservation and energy efficiency.
Section Highlights
• Energy efficiency programs currently serve 156 aMW of load,
representing nearly 12.2% of customer demand.
• More than 3,000 energy efficiency measures and 16 demand response
options are considered for resource selection.
• Avista's solar net metering program includes 4,433 customers generating
with 29.9 megawatts of capacity.
• Community solar, roof-top solar, energy efficiency, demand response and
distributed energy storage are options for utility resource selection.
Energy Efficiency
Avista's energy efficiency programs may provide cost-effective opportunities for
customers to save energy by replacing old equipment with better performing, energy
efficient equipment. The energy efficiency programs offer a wide array of low-cost
measures to our customers. Since 1978, Avista has acquired 275 aMW of energy
efficiency. Currently 156 aMW of this savings remains as a load reduction due to our
efforts becoming code or standard practice. Figure 6.1 illustrates Avista's historical
electricity conservation acquisitions using an average 18-year measure life. The 18-year
measure life accounts for the difference between the cumulative (solid black line) and
online trajectories (dotted black line) where program savings is no longer counted as
energy efficiency. Currently 156 aMW of energy efficiency programs serve customers,
representing nearly 12.2% of 2023 customer load.
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Chapter 6: Distributed Energy Resource Options
Figure 6.1: Historical Conservation Acquisition (System)
25 aMW 280 aMW
240 aMW
20 aMW
e
J�ati�, 200 aMW
GJ� c
rn 15 aMW
c �rrrr 160 aMW
m a
f° ��`• 120 aMW
10 aMW
� U
80 aMW
�r
5 aMW
40 aMW
aMW aMW
O Q LO � 0) fM LO � 0) m In r 0) C2 In O cO
I� O a0 co 00 OD O) m O 0) 0) O O O O O N ('4
O 0) O O m O 0) m O m m O O O O O O O O O O O O
N CONN N N N N N N N N N
Avista provides energy efficiency and educational offerings to the residential (inclusive of
low-income and named communities) commercial and industrial customer segments.
Program delivery mechanisms include prescriptive, site-specific, regional, upstream,
midstream, behavioral, home energy audits, market transformation, and third-party direct
install options. Prescriptive programs provide fixed cash rebate incentives based on an
average savings assumption for the measure across the region. Prescriptive programs
work best where uniform measures or offerings apply to large groups of similar
customers. Examples of prescriptive programs include the installation of qualifying high-
efficiency heating equipment or upgrades to lower U-value windows.
Site-specific programs, or customized offerings, provide cash incentives for cost-effective
energy saving measures or equipment not meeting prescriptive rebate requirements.
Site-specific programs require customized approaches for commercial and industrial
customers because of the unique characteristics of each premise and/or process. Other
delivery methods build off these offerings with up- and mid-stream retail buy-downs of
low-cost measures, free-to-customer direct install programs or coordination with regional
market transformation efforts. In addition to developing and delivering incentive offerings,
Avista also provides technical assistance (in multiple languages where possible) in the
forms of education, outreach, and other resources to customers to encourage
participation in efficiency programs and measures.
The Conservation Potential Assessment
Avista retained Applied Energy Group (AEG) as an independent consultant to assist in
developing a Conservation Potential Assessment (CPA). The CPA is the basis for the
energy efficiency portion of this plan. The CPA identifies the 20-year potential for energy
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Chapter 6: Distributed Energy Resource Options
efficiency in accordance with the Energy Independence Act's (EIA) energy efficiency
goals and provides data on resources specific to Avista's service territory for use in the
resource selection process. The potential assessment considers the impacts of existing
programs, the influence of known building codes and standards, technology
developments and innovations, legislative policy changes to the long-term economic
influences, and energy prices. The CPA report and list of energy efficiency measures is
included in Appendix C.
AEG first developed estimates of technical potential, reflecting the adoption of all
conservation measures, regardless of cost-effectiveness or customers' likeliness to
participate. The next step identifies the estimated achievable technical potential; this
measure modifies the technical potential by accounting for customer adoption constraints
by using the Power Council's 2021 Plan ramp rates. The estimated achievable technical
potential, along with associated costs, feed into the PRiSM model to select cost-effective
measures. AEG took the steps shown in Figure 6.2 to assess and analyze energy
efficiency and potential within Avista's service territory.
Figure 6.2: Analysis Approach Overview
PotentialBase-year End-use Technical Technical Study
Study Objectives 0*�* energy use projection byi\ Achievable
• Potential
•Avista customer •PNWandAEO •NPCC2021Power •NPCC2021Power •IRP inputs from
accounts equipment growth Plan and RTF UES Plan ramp rates PRISM
•NE EA Surveys and purchases Workbook -Avista program -Measure Summary
•Avista GenPOP •Avista load assumptions results
Survey forecasts -Secondary Sources
-Energy Market •Codesand (DEEM)
profiles standards •Avista
-Secondary sources •Secondarydata Accomplishments
AEG's CPA included the following steps:
1. Perform a market characterization to describe sector-level electricity use for the
residential (inclusive of low income), commercial and industrial sectors for the 2023
base year.
2. Develop a baseline projection of energy consumption and peak demand by sector,
by segment and by end use for 2026 through 2045.
3. Define and characterize several hundred conservation measures to be applied to
all sectors, segments and end uses.
4. Estimate technical potential and achievable technical potential at the measure
level in terms of energy and peak demand impacts from conservation measures
for 2026-2045.
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Chapter 6: Distributed Energy Resource Options
Market Segmentation
The CPA considers Avista customers by Washington and Idaho service territories and by
sector. The residential sector includes single-family, multi-family, manufactured homes,
and low-income customers56 using Avista's customer data and U.S. Census data from
the American Community Survey (ACS). For the residential sector, AEG utilized Avista's
customer data and prior CPA ratios developed from census information. AEG
incorporated information from the Northwest Energy Efficiency Alliance's (NEEA)
Commercial Building Stock Assessment to assess the commercial sector by building type,
installed equipment and energy consumption. Avista analyzed the industrial sector for
each state because of their unique energy needs. AEG characterized energy use by end
use within each segment in each sector, including space heating, cooling, lighting, water
heating, or motors; and by technology, including heat pumps and resistance-electric
space heating.
The baseline projection is a "business as usual" metric without future utility conservation
or energy efficiency programs. It estimates annual electricity consumption and peak
demand by customer segment and end use absent future efficiency programs. The
baseline projection includes the impacts of known building codes and energy efficiency
standards as of 2024 when the study began. Codes and standards have direct bearing
on the amount of energy efficiency potential due to the reduction in remaining end uses
with potential for efficiency savings. The baseline projection accounts for market changes
including:
• customer and market growth;
• income growth;
• retail rates forecasts;
• trends in end use and technology saturation levels;
• equipment purchase decisions;
• consumer price elasticity;
• income; and
• persons per household.
For each customer class, AEG compiled a list of electric energy efficiency measures and
equipment, drawing from the Northwest Power and Conservation Council's (NPCC or
Council) 2021 Power Plan, the Regional Technical Forum, and other measures applicable
to Avista. The individual measures included in the CPA represent a wide variety of end
use applications, as well as devices and actions able to reduce customer energy
consumption. The AEG study includes measure costs, energy and capacity savings and
estimated useful life.
56 The low-income threshold for this study is 200% of the federal poverty level. Low-income information is
available from U.S. Census data and the American Community Survey data for Washington customers
only.
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Chapter 6: Distributed Energy Resource Options
Avista, through its PRISM model, considers other performance factors for the list of more
than 3,000 measures and performs an economic screening on each measure for every
year of the study to develop the economic potential for Avista's service territory and
individually by state. Avista supplements energy efficiency activities by including
potentials for distribution efficiency measures consistent with EIA's conservation targets
and the NPCC 2021 Power Plan.
Overview of Energy Efficiency Potential
AEG's approach adhered to the conventions outlined in the National Action Plan for
Energy Efficiency Guide for Conducting Potential Studies.57 The guide represents
comprehensive national industry standard practice for specifying energy efficiency
potential. As shown in Table 6.1, two types of potential results were specifically included
in this study - technical potential and achievable technical potential by state.
Table 6.1: Cumulative Potential Savings (Across All Sectors for Selected Years)
-0 2045
Technical Potential GWh 191.4 387.2 593.7 1,915.5 2,832.2
Washington 128.2 258.8 396.5 1,290.5 1,928.2
Idaho 63.1 128.4 197.2 6295.0 904.0
Total Technical Potential aMW 21.8 44.2 67.8 218.7 323.3
Technical Achievable Potential 86.0 183.2 295.1 1,274.6 2,082.5
Washington 56.6 120.4 194.2 853.4 1,431.0
Idaho 29.4 62.8 100.9 421.2 651.6
Technical Achievable Potential aMW 9.8 20.9 33.7 145.5 237.7
Potential programs must be cost effective to be selected for future implementation. Figure
6.3 illustrates the supply curve of this potential using their associated price per MWh. For
Idaho savings, the potential has a near zero cost using the Utility Cost Test (UCT) method
until approximately 150 GWh, then quickly rises. As for Washington, using the Total
Resource Cost (TRC) method, there is "no cost" energy efficiency until reaching
approximately 300 GWh, then linearly increases until around 1,100 GWh, then goes up
exponentially. The amount of energy efficiency the model selects will be where the supply
curve meets the avoided cost. For example, if Washington's avoided cost were $100 per
MWh, then 600 GWh of energy efficiency would be selected. Avista uses a more
sophisticated resource selection approach, considering each program's individual cost
and benefits compared to alternatives, but the supply curve demonstration is a simplified
cost and benefit illustration of the available energy efficiency.
57 National Action Plan for Energy Efficiency (2007). National Action Plan for Energy Efficiency Vision for
2025: Developing a Framework for Change. https://www.energy.gov/sites/default/files/2023-10/napee-
vision 1.pdf
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Chapter 6: Distributed Energy Resource Options
Figure 6.3: Jurisdiction Supply Curves
$500
$450
$400
$350
t
$300
L
$250
d
$200
$150
$100 -Washington_TRC
$50 -Idaho UCT
$0
0 200 400 600 800 1000 1200 1400 1600 1800
Gigawatt Hours
Technical Potential
Technical potential finds the most energy-efficient option commercially available for each
purchase decision regardless of its cost. This theoretical case provides the broadest and
highest definition of savings potential because it quantifies savings if all current
equipment, processes, and practices in all market sectors were replaced by the most
efficient and feasible technology. The technical potential case is provided for planning
and informational purposes. Technical potential in the CPA is a "phased-in technical
potential," meaning only the current equipment stock at the end of its useful life is
considered and changed out with the most efficient measures available. Non-equipment
measures, such as controls and other devices (e.g., programmable thermostats) phase-
in over time, just like the equipment measures. All measures are implemented according
to ramp rates developed by the Council for its 2021 Power Plan and apply to 100% of the
applicable market.
Technical Achievable Potential
The technical achievable potential refines the technical potential by applying customer
participation rates accounting for market barriers, customer awareness and attitudes,
program maturity, and other factors affecting market penetration of energy efficiency
measures. AEG used ramp rates from the Council's 2021 Power Plan in development of
the technical achievable potential.
For the technical achievable potential case, a maximum achievability multiplier of 85% to
100% is applied to the ramp rate per Council methodology. This factor represents a
reasonable achievable potential to be acquired through available mechanisms,
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Chapter 6: Distributed Energy Resource Options
regardless of how energy efficiency is achieved. Thus, the market applicability
assumptions utilized in this study include savings outside of utility programs. Avista uses
technical achievable potential as an input to its resource selection.
Integrating Results into Business Planning and Operations
The CPA and IRP energy efficiency evaluation processes provide high-level estimates of
cost-effective acquisition opportunities. These results establish baseline goals for
continued development and enhancement of energy efficiency programs, but do not
provide enough detail to form an actionable acquisition plan. Avista uses results from both
processes to establish a budget for energy efficiency measures, determine the size and
skillsets necessary for future operations, and identify general target markets for energy
efficiency programs. This section discusses recent operations of the individual sectors
and energy efficiency business planning.
The CPA's economic potential is used for implementing energy efficiency programs to:
• Identify conservation resource potentials by sector, segment, end use, and
measure. Energy efficiency staff uses CPA results to determine the segments and
end uses/measures to target.
• Identify measures with the highest benefit-cost ratios to help the utility acquire the
highest benefits for the lowest cost. Ratios evaluated include TRC in Washington
and UCT in Idaho.
• Identify and target measures with large potential but significant adoption barriers
that the utility may be well-positioned to address through innovative program
design or market transformation efforts.
• Optimize the efficiency program portfolio by analyzing cost effectiveness, potential
of current measures and programs; and by determining potential new programs,
program changes and program sunsets.
The CPA's economic potential illustrates potential markets and provides a list of cost-
effective measures to analyze through the ongoing energy efficiency business planning
process. This review of both residential and non-residential program concepts and
sensitivity provides more detailed assumptions feeding into program planning.
Residential Sector Overview
Avista's residential portfolio of efficiency programs engages and encourages customers
to consider energy efficiency improvements for their home. Prescriptive rebate programs
are the main component of this portfolio, augmented with other offerings, including
midstream select distribution of low-cost lighting and weatherization materials, direct-
install programs as well as multi-faceted, multichannel outreach and customer
engagement.
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Residential customers received more than $2.3 million in Avista rebates in 2023 to offset
the cost of implementing energy efficiency measures. All programs within the residential
portfolio contributed 7,122 MWh to the 2023 annual first-year energy savings.
Low-Income Sector Overview
Currently, Avista leverages the infrastructure of several network Community Action
Agencies (CAAs) and one tribal weatherization organization to deliver energy efficiency
programs for low-income residential customers in Avista's service territory. CAAs have
resources to income qualify, prioritize, and treat clients' homes based upon several
characteristics beyond Avista's ability to reach. These agencies also have other
resources to leverage for home weatherization and energy efficiency measures beyond
Avista's contributions. The agencies have in-house and/or contract crews available to
install many of the efficiency program measures.
Avista's general outreach for this sector is a "high touch" customer experience for
vulnerable customer groups including, but not limited to seniors, low-income, and those
in Named Communities. Each outreach encounter includes information about bill payment
options and energy management tips, along with the distribution of low-cost
weatherization materials. Avista partners with community organizations to reach these
customers through community resource events, at area food banks/pantry distribution
sites, senior activity centers, or affordable housing developments. Low-income energy
efficiency programs contributed 622 MWh of annual first-year electricity savings in 2023.
Non-Residential Sector Overview
Non-residential energy efficiency programs deliver energy efficiency through a
combination of prescriptive and site-specific offerings. Any measure not offered through
a prescriptive program is eligible for analysis through the site-specific program, subject to
the criteria for program participation. Prescriptive paths for the non-residential market are
preferred for small and uniform measures, but larger measures may also fit where
customers, equipment, and estimated savings lack uniformity.
More than 5,100 prescriptive and site-specific nonresidential projects received funding in
2023. Avista contributed approximately $21.1 million for energy efficiency upgrades to
offset costs of non-residential applications and realized over 49,139 MWh in annual first-
year energy savings in 2023.
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Demand Response
Current Demand Response Programs and Pilots
Avista's current Demand Response (DR) resources include residential and general
service Time-of-Use (TOU) rates and Peak Time Rebate (PTR) pilots, commercial
Electric Vehicle (EV) TOU rates and one bilateral agreement with an industrial customer
for 30 MW. The industrial customer agreement was executed in 2022 for a four-year term
with provisions to extend it another six-years. Avista is also working with NEEA and other
utilities in the region on an End Use Load Flexibility (EULF) pilot with a focus on direct
load control for grid-enabled water heaters and line voltage thermostats. These pilots will
influence future IRPs, just as past pilot experience influenced this IRP.
Historical Demand Response Programs and Pilots
Avista piloted DR technologies between 2007 and 2009, to examine cost-effectiveness
and customer acceptance. The pilot tested scalable Direct Load Control (DLC) devices
based on installations in approximately 100 volunteer households in Sandpoint and
Moscow, Idaho. The sample allowed Avista to test DR with the benefits of a larger-scale
project, but in a controlled, measurable, and customer-friendly manner. Avista installed
DLC devices on residential heat pumps, water heaters, electric forced-air furnaces, and
air conditioners to control operations during 10 scheduled events at peak times ranging
from two-to-four hours. A separate group, within the same communities, participated in
an in-home-display device study as part of the pilot. The program offered Avista and its
customers hands-on experience with equipment that provides "near-real time" feedback
on energy usage. The insights from the pilot study are detailed in a report submitted to
the Idaho Public Utilities Commission.58
Avista was part of the 2009 to 2014 Northwest Regional Smart Grid Demonstration
Project (SGDP) with Washington State University (WSU) and approximately 70
residential customers in Pullman and Albion, Washington. Residential customer assets
included forced-air electric furnaces, heat pumps, and central air-conditioning units. A
non-traditional DLC approach was used, meaning the DR events were not prescheduled,
but rather Avista controlled customer load through an automated process based on utility
or regional grid needs while using predefined customer preferences.59 More importantly,
the technology used in the DR portion of the SGDP predicted if equipment was available
for participation in the control event, providing real time feedback of the actual load
reduction due to the DR event. Additionally, WSU facility operators had instantaneous
feedback due to the integration between Avista and their building management system.
Residential customer notifications of the DR events occurred via customers' smart
thermostat. Avista reported information gained from this project to the prime sponsor for
use in the SGDP's final project report and compilation with other SGDP initiatives.so
58 20100303FINAL REPORT.pdf(idaho.gov)
59 For example, no more than a two-degree Fahrenheit offset for residential customers and an energy
management system at WSU with a console operator.
so Front Matter.pdf(energy.gov)
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Experiences from both pilots showed high customer engagement; however, recruiting
participants was challenging. Avista's service territory has a high level of natural gas
adoption meaning many customers cannot participate in typical DLC electric space and
water heat programs because they have natural gas appliances. Additionally, customers
did not seem overly interested in the DLC programs offered. Bonneville Power
Administration (BPA) found similar customer interest challenges in their regional DLC
programs.61
Avista paid customers direct incentives for program participation in both DLC pilots. A
premium incentive to recruit and retain customers was provided and was not intended to
be scalable. Avista will need additional analysis to determine cost effective payment
strategies beyond pilots to mass-market DLC programs. If Avista is not able to harness
adequate customer interest at cost-effective incentive levels, the future of DR could be
more limited than assumed in this plan.
f)Pmanrl RPcnnncP PntPntial AccPssmPnt Rfiiriv
Avista retained AEG to study the DR potential for Avista's Washington and Idaho service
territories for this IRP. The study estimates the magnitude, timing, and costs of DR
resources likely available to Avista for meeting both winter and summer peak loads.
Figure 6.4 outlines AEG's approach to determine the potential size of DR programs
available in Avista's service territory. Many DR programs require Advanced Metering
Infrastructure (AMI) for billing purposes. All DR pricing programs, behavioral and third-
party contract programs included in this study require AMI as an enabling technology.
The AMI deployment is complete in Washington, and AEG broadly assumes Avista would
follow with AMI metering in Idaho beginning in 2026 (potentially) with a three-year ramp
rate for full deployment, finishing in 2029.
AEG used the same market characterization for this potential assessment study as used
in the CPA. This became the basis for customer segmentation to determine the number
of eligible customers in each market segment for potential DR program participation and
provided consideration for DR program interactions with energy efficiency programs. The
study compared Avista's market segments to national DR programs to identify relevant
DR programs for analysis.
Lastly, for the pilot programs included in the potential, AEG based on program roll-out
beginning in 2024 and includes TOU rate options, PTR, and DLC of grid-enabled water
heaters. AEG forecasted the potential program savings as if the programs matured and
operated through 2045. Each pricing pilot will run for two years. The DLC grid-enabled
water heater pilot is a project Avista is participating in with several other regional utilities
and led by NEEA.
61 BPA's partnership with Kootenai Electric Coop, Report (bpa.gov).
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Figure 6A Program Characterization Process
AMI Select M Program ' Develop
Infrastructure Appropriate Characterization Program
Analysis Programs •Develop participation Hierarchy
•AMI is required for •Develop a list of rates, impacts, cost, •Ensure the potential
participation in appropriate and other key is not double
certain programs programs program parameter counted between
•Determines eligible programs
populations for rate •Rates, direct load •In the context of high
based options control, interruptible, and low potential
-Analysis assumes all economic,and cases
large C&I customers storage options
in the state have
Interval Demand
Recorder(IDR)
meters
Demand Response Programs
This potential process identifies several DR program options shown in Table 6.2. The
different types of DR programs include two broad classifications: curtailable/controllable
DR and rate design programs. Except for the behavioral program, curtailable/controllable
DR programs represent firm, dispatchable and reliable resources to meet peak-period
loads. This category includes DLC, Firm Curtailment (FC), thermal and battery storage
(virtual power plant). Rate design options offer non-firm load reductions that might not be
available when needed but still create a reliable pattern of potential load reduction. Pricing
options include TOU, PTR, and variable peak pricing. Each option requires a new rate
tariff for each state in Avista's service territory.
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Table 6.2: Demand Response Program Options by Market Segment
ProgramFIN- DR Progranj[ Participating Market Segment Season Impacted
. Large
Curtailable/ DLC Central AC X X X
Controllable DLC Smart X X X
DR Thermostat—Cooling
DLC Smart X X X
Thermostat— Heating
DLC CTA-2045 X X X X
Water Heating
DLC Water Heating X X X X
DLC Smart X X X X
Appliances
EV VG1 Telematics X X X
Behavioral
Third Party Contracts X X X X
Thermal Energy X X X X
Storage
Battery Energy X X X X X X
Storage
Behavioral X X X
Ancillary Services X X X X X X
Rates Time-of-Use Opt-in X X X X X X
Time-of-Use Opt-out X X X X X X
Variable Peak Pricing X X X X X X
Rates
Peak-Time Rebate X X X X
Electric Vehicle X X X X X
Time-of-Use
Direct Load Control
DLC programs require an enabling technology to drive load change for Avista's residential
and general service customers in Idaho and Washington and allow Avista to directly
control a variety of customer end-use appliances during capacity constrained hours. For
example, DLC smart thermostat programs would leverage a customer's smart thermostat
installation and rely on the customer's Wi-Fi for communications with the grid and utility.
Likewise, DLC smart appliances (refrigerators, clothes washers, and dryers), DLC central
air conditioning, DLC water heating, and DLC CTA-2045 water heating programs assume
controlling the device enables a version of a load control for the utility. Typically, DLC
programs take five years to mature to maximum participation levels and AMI technology
is preferred to evaluate and measure event response and system impacts.
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Third Party Contracts - Firm Curtailment
Customers participating in a firm curtailment program agree to reduce demand by a
specific amount or to a pre-specified consumption level during a capacity constrained
event in exchange for fixed incentive payments. Customers receive payments while
participating in the program even if they never receive a load curtailment request while
enrolled in the program. This capacity payment typically varies with the firm reliability-
commitment level. In addition to fixed capacity payments, participants receive
compensation for reduced energy consumption. Because the program includes a
contractual agreement for a specific level of load reduction, enrolled loads have the
potential to replace a firm generation resource.
Customers with maximum demand greater than 200 kW and operational flexibility are
attractive candidates for firm curtailment programs. Examples of customer segments with
high participation possibilities include large retail establishments, grocery chains, large
offices, refrigerated warehouses, water- and wastewater-treatment plants, and industries
with process storage (e.g., pulp and paper, cement manufacturing). Customers with
operations requiring continuous processes, or with relatively inflexible obligations, such
as schools and hospitals, generally are not good candidates for curtailment programs.
These assumptions determine the eligible population for participation in this program and
the study assumes a third party would administer all aspects of the program.
Thermal Energy Storage
Thermal energy storage (TES) stores thermal energy (hot or cold) for later use and can
be used to balance energy demand between different times of the day. It has primarily
been used in non-residential buildings but, as technology advances, may have the
potential for future use in residential applications. TES technologies can include sensible
heat storage (storing energy by heating or cooling a material), latent heat storage (using
phase-change materials to store energy from solid to liquid) and thermo-chemical storage
(using chemical reactions to store and release energy). As an example of latent heat
storage, a variable speed fan can automatically circulate the cool air throughout a room
using the stored energy (ice) rather than having to draw energy from the grid during peak
times to chill the air.
Battery Energy Storage (Virtual Power Plant)
Battery energy storage technologies draw electricity during low demand periods and store
it for later use during capacity constrained periods. The program assumes customers own
the batteries as part of their on-site renewable generation system. An incentive can be
offered to help cover part of the installation costs of the battery system. Once enrolled in
the program (i.e. virtual power plant), customers allow the utility to automatically manage
(charge/discharge) the battery during capacity constrained periods in exchange for an
annual participation payment.
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Behavioral
A behavioral DR program is a voluntary reduction in response to digital behavioral
messaging. The program sends notifications requesting customers to reduce usage via
text or email messages. To minimize costs, the plan assumes the program would work in
tandem with an energy efficiency behavioral reporting program. Also required for the
program is AMI technology to evaluate and measure the impact of the program events.
Behavioral EV V1G Telematics
This concept pays a monthly incentive to change charging behavior using the EV on-
board charging system. If customers charge during on-peak hours no more than three
times per month a customer would receive an incentive. After one-year the incentives
end, but it is assumed off-peak charging behavior is set and will continue.
Time of Use Rates (Opt-in)
A TOU rate is a time-varying energy rate. Relative to a revenue-equivalent flat rate, the
TOU rate is higher during either higher load or price periods, while the rate during other
periods is lower. This provides customers with an incentive to shift energy consumption
out of the higher-price on-peak hours to the lower cost off-peak hours. TOU is not a DR
option, per se, but rather a pricing program to encourage a change in behavior. Large
price differentials are generally more effective than smaller differentials for TOU programs
and AMI is required.
The DR study considered two types of TOU pricing options. In an opt-in rate, participants
voluntarily enroll in the rate. An opt-out rate places all customers on the time-varying rate,
but they may opt-out and select another rate later.
Two Opt-in TOU rate designs are being piloted in Washington State for residential and
general service customers. The pilots began in June 2024 and will run for two years.
Evaluations will be conducted to determine how Avista can deploy cost effective TOU
programs more broadly post-pilot. Avista did not model TOU-opt out due to lower long-
term capacity savings than the opt-in program design.
Variable Peak Pricing
The Variable Peak Pricing (VPP) is an option under a TOU program where the rate
amount changes daily to reflect system conditions and costs for peak hours. Under a VPP
program, on-peak prices for each weekday are made available the previous day. Through
the VPP program, customers are billed for their actual consumption during the billing cycle
at these prices. Over time, establishment of event-trigger criteria enables customers to
anticipate events based on extreme weather or other factors. System contingencies and
emergency needs are good candidates for VPP events. VPP program participants are
required to be enrolled in a TOU rate option.
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Peak Time Rebate
Participation in a Peak-Time-Rebate (PTR) program is voluntary. In an event, participants
are notified a day in advance for a two- to six-hour event period during peak hours. If
customers do not participate, there is no penalty. If they do participate, they receive a bill
credit based on the amount of energy reduced as compared to a calculated baseline.
PTR is dependent on enrollment in other DR programs to avoid double counting of
savings, but like the other pricing programs, it does require AMI for billing purposes.
A PTR program is being piloted in Washington State for residential and general service
customers. The pilots began in June 2024 and will run for two years. Evaluations will be
conducted to determine how Avista can deploy cost effective PTR programs more broadly
post-pilot.
Electric Vehicle Time of Use
Rather than a typical TOU rate applying on/off peak prices to the whole customer's usage,
the EV TOU rate program applies on/off peak prices exclusively to the EV load. This
program requires EVs to be metered separately. Avista currently offers this rate option in
Wahington and when AMI is available in Idaho, a similar pricing program could be
available.
Demand Response Program Participation
AEG's forecast for DR potential uses a database of existing program information and
insights from market research results representing "best-practice" estimates for program
participation. The industry commonly follows this approach for arriving at achievable
potential estimates. However, practical implementation experience suggests there are
uncertainties in factors such as market conditions, regulatory climate, the economic
environment, and customer sentiments influencing participation in DR programs.
DR options require time to mature to a steady state because of the time needed for
customer education, outreach, and recruitment. Further, the physical implementation and
installation of any hardware, software, telemetry, or other enabling equipment will require
time for implementation. DR programs included in the AEG study have ramp rates
generally with a three-to-five-year timeframe before reaching the steady state.
Table 6.3 shows the steady-state participation rate assumptions for each DR program
option. Space cooling is split between DLC central AC and smart thermostat options.
Likewise, eligible EV charging for general service customers are split between the TOU
(opt-in or opt-out) programs and the EV TOU program. Eligible customers for each
customer class are calculated based on market characterization and equipment end use
saturation.62
62 See the Demand Response Potential Appendix found within the 2022-2045 Avista Electric CPA found in
Appendix C.
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Chapter 6: Distributed Energy Resource Options
Table 6.3: DR Program Steady-State Participatiun Kates (% of Eligible Customers)
D- Program ResidentialLarge
Service Service/ General Large
Small Service General
Direct Load Control (DLC) of central AC 10% 10% - -
DLC of domestic hot water heaters (DHW) 15% 5% - -
Smart Thermostats DLC Heating 5% 3% - -
CTA-2045 hot water heaters 50% 50% - -
Smart Thermostats DLC Cooling 20% 10% - -
Smart Appliances DLC 5% 5% - -
Third Party Contracts - 15% 15%
EV V1 G Telematics 20% - - -
DLC Electric Vehicle Charging 13% 7%
Time-of-Use Pricing Opt-in 20% 20%
Time-of-Use Pricing Opt-out - - 25% 25%
Variable Peak Pricing 15% 15% - -
Peak-Time Rebate - 20% 10% -
Electric Vehicle Time-of-Use - 0.5% 1.5% 1.5%
Thermal Energy Storage 50% 50%
Battery Energy Storage 20% - - -
Behavioral 10% 10% - -
Cost d11U rotential Assumptions
Each DR program in this evaluation is assigned an average load reduction per participant
per event, an estimated duration of each event, and a total number of event hours per
year. Costs are also assigned to each DR program for annual marketing, recruitment,
incentives, program development, and administrative support. These assumptions result
in potential demand savings and total cost estimates for each program independently and
on a standalone basis.
If Avista offers more than one DR program, the potential for double counting savings from
DR programs exists. To address this possibility, a participation hierarchy assumes an
integrated approach where program savings are based upon many programs being
available. These savings and costs results were then used in Avista's modeling. See
Appendix C for additional detail on DR resource assumptions used in developing potential
savings and cost results.
The estimated savings for each program and its levelized costs are shown in Table 6.4.
The cost of the programs within this table represents the on-going operations and capital
cost required to start and maintain these programs for programs beginning in 2026. The
capital costs are amortized and recovered over a 10-year period. These tables include
the estimated potential megawatt savings for 2030 and 2045 to illustrate program
potential. These estimates are the expected amount of demand reduction from all
program participants using an "integrated" methodology, whereas potential may be higher
for a program where only one program is in place. It is also worth noting these savings
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Chapter 6: Distributed Energy Resource Options
are net demand savings rather than the higher amount of load needed under contract to
realize these savings.
Table 6.4: System Program Cost and Potei
ProgramLm�L2030 2045 2030 2045
Battery Energy Storage $35.6 3.1 13.0 3.0 12.7
Behavioral $148.0 3.0 3.2 2.1 2.2
DLC Central AC $166.7 - - 11.6 15.4
EV V1 G Telematics $430.2 9.1 47.1 9.1 47.1
DLC Smart Appliances $341.7 3.2 4.0 3.2 4.0
DLC Smart Thermostats - Cooling $482.6 - - 24.7 33.4
DLC Smart Thermostats - Heating $30.6 9.2 14.6 - -
DLC Water Heating $634.7 2.8 3.5 2.8 3.5
CTA-2045 ERWH $154.1 3.4 5.6 1.5 2.4
CTA-2045 HPWH $538.1 0.5 13.2 0.3 8.5
Thermal Energy Storage $783.7 - - 0.6 0.6
Third Party Contracts $101.4 17.7 21.0 22.4 26.6
Time-of-Use Opt-in $217.1 3.4 4.2 2.4 3.0
EV TOU Opt-in $40.4 1.2 9.6 1.2 9.6
VPP Rates $21.6 4.8 5.7 6.1 7.2
Peak Time Rebate $78.5 7.9 10.1 6.1 7.9
Total Potential 69.2 1 154.8 97.1 1 184.2
There are a few other factors Avista considers when evaluating DR programs, the first is
the energy value of the program. Some program opportunities reduce energy usage
permanently, but most programs have snap back load where additional energy usage
returns after the DR event. Avista determined the net value of these load changes using
hourly wholesale market prices discussed in Chapter . compared to a time series of how
the load profile would change if the DR program was dispatched.
The second major factor related to whether a program is cost effective considers the
program's ability, compared to alternatives, to qualify as load reduction or the program's
Qualifying Capacity Credit (QCC). The QCC is uncertain for these types of programs in
the future Western Resource Adequacy Market (WRAP). This analysis assumes a 6-hour
reduction is required to receive 100% QCC, whereas the QCC is a percentage of the hour
reduction. For example, a 4-hour program is 67% and a 3-hour program is 50%. The QCC
values are increased by the PRM to account for peak load reduction. Effectively this new
change gives DR programs a higher capacity benefit compared to the 2023 IRP analysis.
Avista is uncertain if DR programs will be as valuable today as in the future when the
region has more capacity limited resources. To account for this potential lost QCC value,
DR is reduced 20% linearly between 2030 and 2045 from the 2026 value.
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Chapter 6: Distributed Energy Resource Options
Distributed Generation Resources
Customer-Owned Generation
Avista has 4,433 customer-installed net-metered generation projects on its system as of
December 2023, representing a total installed capacity of 29.9 MW. Approximately 89%
percent of installations are in Washington; most are in Spokane County. Figure 6.5 shows
annual energy production. The estimated actual is based on on-line capacity, while the
forecasted generation is an estimate from the DER potential assessment study. Solar is
the primary net metered technology followed by wind, combined solar and wind systems,
and biogas. The average size of customer installations is 6.7 kilowatts. In Idaho, solar
installation rates continue to increase without a major state subsidy, but as of December
2023, only 596 Idaho customers participate as compared to Washington's 3,837
customers.
Figure 6.5: Avista's Net Metering Generation (aMW)
40
Estimated Actual Forecasted
35
I
I
30 I-
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25 ._�.
3 I
m 20
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CD CD CD CDO O CDO O O O O O O O O O CDO CD CD CD O CD CD O CD CDO O CD CDO CD CD CD CD CDO O O O O
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
Net-metered installations are exponentially increasing due to federal incentives,
increasing solar vendor sales, environmental concerns, rising energy costs, and expiring
state incentives. If the growth of net-metering customers continues to increase, Avista
may need to adjust rate structures for these customers. Much of the cost of utility
infrastructure to support reliable energy delivery is recovered in energy rates. Net
metering customers continue to benefit from this infrastructure but are no longer
purchasing as much energy, thereby transferring some of their grid infrastructure costs to
customers not generating their own power.
Avista-Owned Solar
Avista operates three small solar DER projects. The first solar project is three kilowatts
located at its corporate headquarters. Avista installed a 15-kilowatt solar system in
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Chapter 6: Distributed Energy Resource Options
Rathdrum, Idaho to supply its My Clean EnergyTM (formerly Buck-A-Block) voluntary
green energy program. The 423-kW Avista Community Solar project, located at the
Boulder Park property, began service in 2015.
-�' - " C• "vista-Owned Solar Resource Capability
Project Name Project Location Project Capacity
Spokane Headquarters Solar Spokane, WA 4
Rathdrum Solar Rathdrum, ID 15
Boulder Park Solar Spokane Valley, WA 423
Total 442
Solar Generation & Storage Opportunities
This IRP includes both utility owned distribution-sized solar generation and storage for
residential, commercial, and community sized projects as resource options. Customer
and distribution sized resources have gained traction to promote equitable outcomes for
specific communities or to solve local supply issues. For this analysis these DERs are
included as resource options for the Named Community Investment Fund (NCIF) but they
can also be selected if cost effective without the additional funding. The resource
configurations and costs are shown in Table 6.6. The costs are shown in nominal Ievelized
cost dollars and include the benefits of the Inflation Reduction Act (IRA) through 2033,
cost assumptions are based on information provided by TAC members and the 2023
National Renewable Energy Laboratory (NREL) resource cost study.63 A low-income
community solar option is based on the expected net cost to Avista customers after
accounting for grants provided by the State of Washington. The costs are Ievelized cost
of energy for solar resources over the life of the asset and costs for energy storage is the
Ievelized cost of capacity over 20 years including battery reconditioning.
63 NREL (National Renewable Energy Laboratory). 2023. 2023 Annual Technology Baseline. Golden, CO:
National Renewable Energy Laboratory. Technologies I Electricity 12023 1 ATB I NREL
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Chapter 6: Distributed Energy Resource Options
Table 6.6: DER Generation & Storage Options Size and Cost
Project Name . ', .',
Month month
Existing res. building solar 166 287 - -
Existing res. building solar with storage 166 287 24.99 42.51
New res. building solar 154 266 - -
New res. building solar with storage 154 266 23.62 39.92
Com. building solar 120 1 140 - -
Com. building solar with storage 120 140 26.88 38.19
Utility owned solar array 59 68 - -
Utility owned solar array with storage 59 68 17.83 21.34
Stand-alone energy storage (4hr) - - 17.34 25.38
Stand-alone energy storage 8hr - - 30.89 44.17
Low-income Community Solar Program 27 68 - -
DER Evaluation Methodology
Avista models each of the DERs discussed in this chapter in the same economic selection
model as other utility asset options. Avista's includes all known utility costs and, where
required (i.e., Washington), known non-energy or social impacts. The Washington Utilities
and Transportation Commission (UTC) is developing a proposa164 for evaluating DERs
as part of a workshop process with the assistance of Synapse Energy Economics.
Currently, the UTC has put out draft proposals of the types of considerations utilities
should use when conducting resource planning activities through a workshop series and
has sought comments from utilities. While this concept continues to be in draft form, it
provides an opportunity for Avista to demonstrate the types of costs and considerations
used in the evaluation of these resources. The list of options from the strawman proposal
is shown in Table 6.7 for those resources applicable to this plan.
Due to the complexity and size of the list of considerations, the answers within the boxes
are high level. "Direct" means there is a value used within the PRiSM optimization model
for this value. "Indirect" indicates this value is included by the savings compared to other
resources; for example, if choosing energy efficiency lowers capacity needs from other
resources. Items listed as "N/A" indicate the values are not applicable to the DER. "No"
indicates the value is not included. Many of the values discussed are qualitative and
difficult to quantify for use in modeling.
64 Washington Cost-Effectiveness Test for Distributed Energy Resources, Straw Proposal for the Primary
Test, November 7, 2022. Docket UE-210804.
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Table 6.7: DER Cost and Bu,writ Impacts
ResponseCategory Impact Energy Demand Solar Storage
Efficiency
Generation Energy Generation Direct Direct Direct Direct
Capacity Indirect Indirect Direct Direct
Environmental Compliance Indirect Indirect Indirect Indirect
Clean Energy Compliance Indirect Indirect Direct Indirect
Market Price Effects Direct Direct Direct Direct
Ancillary Services Indirect Indirect Direct Direct
Transmission Transmission Capacity Direct Indirect Direct Direct
Transmission System Losses Direct Direct Direct Direct
Distribution Distribution Cost Direct Direct Direct Direct
Distribution Voltage No No Indirect Indirect
Distribution System Losses Direct Direct Direct Direct
General Financial Incentives N/A Direct No No
Program Admin Cost Direct Direct Direct No
Utility Performance Incentives No No No No
Compensation Mechanisms No No No No
Credit and Collection Costs Indirect Indirect Indirect Indirect
Risk No No No No
Reliability No No No No
Resilience No No No No
Host Measure Costs Direct Direct N/A N/A
Customer Transaction Costs Direct Direct N/A N/A
Energy Interconnection Fees N/A N/A Direct Direct
Impacts Risk No No No No
Reliability No No No No
Resilience No No No No
Other Fuels n/a No No No
Tax Incentives Direct No Direct Direct
Host Water No No No No
Customer Asset Value Indirect No No No
Non-Energy Productivity Direct No No No
Impacts Economic well-being Direct No No No
Comfort Direct No No No
Health & Safety Direct No No No
Empowerment& Control No No No No
Satisfaction & Pride Indirect No No No
Low-Income NEls Direct No No No
Societal Greenhouse Gas Emissions Direct Indirect Indirect Indirect
Impacts Other Environmental No No No No
Public Health Direct No Direct Direct
Economic & Jobs Direct No Direct Direct
Resilience No No No No
Energy Security No No No No
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DER Potential Study
As part of the Washington CEIP approval process,65 Avista agreed to conduct a
distribution level analysis of DER opportunities within its Washington service territory.
This includes a distribution feeder level analysis of future availability and likely adoption
of resources and load changes. The analysis was completed in 2024 and will be used in
future distribution planning activities. Avista hired AEG, who subcontracted with Cadeo,
to conduct this analysis. The planned work covered both electric transportation and
customer owned generation as shown in the list below. The study also included a scenario
regarding upper limits of Named Community DER potential by removing income
limitations. This scenario considers Named Community areas have the same DER
penetration as non-Named Community areas to provide a high case scenario in the event
of incentives for areas with lower incomes.
• EVs
o Local charging: light, medium, heavy duty
o Charging related to interstate travel
• New Generation and Storage
o Residential and commercial solar
o Residential and commercial storage
o Other renewables (wind, small hydro, or other technologies)
The DER potential study contemplated a downscaled distribution level energy efficiency
and DR forecast using the CPA/DR potential. Unfortunately, there is not a useful way to
complete this task in a reasonable time and budget for the entire system. Avista proposes
this future DER analysis should only include feeders with potential capacity constraints
with needs reflecting either DR or energy efficiency as a solution.
DER Study Results
The reference scenario in Table 6.8 summarizes the 2045 DER potential results. The
residential and fleet electric vehicle supply equipment (EVSE) will have the most
significant load impacts in Avista's Washington service territory adding nearly 1,700 GWh
of energy consumption in 2045. Customer solar will decrease energy consumption by
almost 130 GWh in 2045. The term "peak" in the chart refers to a planning peak beginning
at 17:00 and ending at 18:00 local time.
65 Condition 14: Avista will include a Distributed Energy Resources (DERs) potential assessment for each
distribution feeder no later than its 2025 electric IRP. Avista will develop a scope of work for this project no
later than the end of 2022, including input from the IRP TAC, EEAG, and DPAG. The assessment will
include a low-income DER potential assessment. Avista will document its DER potential assessment work
in the Company's 2023 IRP Progress Report in the form of a project plan, including project schedule, interim
milestones, and explanations of how these efforts address WAC 480-100-620(3)(b)(iii) and (iv).
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Table 6.8: Summary Results for 204a, Keference Scu,id, u
DecemberResource Capacity Annual Share of July
. . . Nameplate
NamedImpact Capacity in Load Load
k, & j Community (MW) (MW)
impact Impact
Customer Solar 105 -127 46% -33 0
Customer Battery Storage 96 2 58% -3 -9
Customer Wind 1 -0.3 45% -0.1 0
Residential EVSE 1,544 853 38% 62 62
Fleet EVSE 1 692 1 841 1 67% 1 101 1 105
Public and Workplace EVSE 171 206 60% 33 33
Study Recommendations
As the team notes in the Utility Survey Memo (Appendix B of the DER study found in
Appendix D), the current state of DER potential forecasting highlights many of Avista's
data gaps. The AEG team recommends six actions Avista can take before the next
iteration of the DER potential study to increase the fidelity and depth of insights from a
future location-specific study.
1) Address Fleet Data Gaps. For this study, the team estimated the size and location
of commercial fleets using two methods. First, Avista surveyed commercial vehicle
fleets in its service territory, identifying dozens of smaller fleets. Additionally, the
team used secondary data and satellite imagery to identify many larger fleets in
the service territory, including school district buses and parcel delivery vehicles.
While these efforts successfully obtained data from dozens of fleets, they are not
comprehensive and likely undercount smaller light duty vehicle fleets. Three
activities the team recommends Avista pursue to collect additional fleet data
include:
• Continued outreach to fleet operators. Avista has begun outreach to fleet
operators in its service territory to understand their electrification plans and
possible charging locations. Collecting and refining data from these outreach
activities will advance Avista's ability to inform forecasting studies.
• Analysis of satellite imagery. Though an imperfect indicator of the presence
of vehicle fleets, satellite imagery is a low-effort method of identifying fleets at
Avista's commercial and industrial service points. Collecting and enhancing
data from an analysis of satellite imagery will advance Avista's ability to inform
forecasting studies.
• Acquire fleet inventory data. Washington's Department of Ecology is
currently conducting a fleet inventory that requires fleets with five or more
vehicles to register vehicle types, counts, and depot locations. The team
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recommends that Avista pursue this data source for its service territory when it
becomes available.
2) Develop Commercial EV Charging Profiles. Limited data are available to
characterize EVSE charging profiles, especially for commercial fleets. The AEG
Team recommends that Avista conduct load research on commercial fleet
charging.
3) Develop Seasonal EV Charging Profiles. The team did not have sufficient data
to characterize seasonal differences in EV charging profiles (kW per hour) and
driving patterns (vehicle miles traveled per day), so AEG assumed the summer
and winter charging profiles are the same in Avista's service territory. However,
the winter charging profile could be more significant due to vehicle cabin space
heating or smaller because of less EV driving in the winter. Therefore, AEG
recommended that Avista conduct load research on seasonal EV charging.
4) Conduct Additional Scenario Analyses. The DER adoption forecast analyzed
two scenarios: a reference scenario and a high-incentive scenario. Consider
adding additional scenarios to study the impacts of climate change (e.g., weather,
customer grid resiliency) and ancillary services incentives on DER forecasting.
Integrate the DER and DR Potential Studies. Some types of DERs, like EV
charging and customer battery storage, can be leveraged in DR events. Therefore,
it would benefit Avista to integrate its DER and DR potential studies to avoid
overestimating or underestimating the combined potential.
5) Consider Adding Building Electrification. Building electrification and load
flexibility can affect customer's decisions regarding DER installations. Therefore,
including building electrification and associated load control measures (e.g.,
connected thermostats, heat pump water heater switches) in future DER potential
studies would provide Avista with a more comprehensive understanding of
customer load growth and opportunities to shape it with programs and rates.
6) Consider Adding Emerging Technologies. Emerging technologies, such as
autonomous vehicles and vehicle-to-grid technologies, can change customer
energy consumption patterns. Therefore, in future DER potential studies, Avista
may want to consider emerging technologies as they become commercially
available.
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Named Communities Investment Fund
Chapter 4 of the Company's 2021 CEIP identified the specific actions Avista will
undertake to meet the four-year interim targets to ensure community benefits are
recognized and progress on Customer Benefit Indicators (CBIs) are addressed. This
chapter outlines programs and initiatives demonstrating the Company's commitment of
efforts and resources to ensure the benefits of the Company's transition to cleaner energy
are extended to all, especially those who are members of Named Communities. As part
of this commitment, Avista is investing 1% of total electric retail revenues or approximately
$5 million through the NCIF annually as shown in Table 6.9.
Table 6.9: NCIF Spending by Category
CategoryNCIF Amount NCIF
40% or up to $2 million Energy Efficiency Supplement
20% or up to $1 million Distribution Resiliency
20% or up to $1 million Customer&Third-Party Grants & Incentives
10% or up to $0.5 million Outreach & Engagement
10% or up to $0.5 million Other Projects, Programs, or Initiatives
The utilization of the NCIF will include guidance from its equity and community-based
partners, specifically the Equity Advisory Group (EAG). In its founding year, the EAG
played a critical role in identifying CBIs and defining Vulnerable Populations. It continues
to be a vital partner for providing equity guidance considerations for a variety of Avista's
programs and projects to help assure an equitable clean energy transformation for all
customers. Avista is enthusiastic about assisting and supporting all customers,
especially those in Named Communities in the equitable transition to clean energy by
leveraging the NCIF.
Early in 2023, the EAG participated in a Results Based Accountability (RBA) activity to
identify and prioritize energy efficiency initiatives for Named Communities and identified
the following priorities:
• Improve awareness and energy efficiency for Spokane Tribe, multi-
family, and manufactured homes.
• Increase tree canopy.
• Increase access to energy efficiency products and appliances.
• Increase awareness and engagement in energy efficiency programs.
• Match funds for energy efficiency grant applications to community-
based organizations and tribal partners.
• Improve energy efficiency for those without stable housing.
The group's prioritized initiatives for the energy efficiency NCIF grants focus to closely
align with the Specific Actions identified in Chapter 4 of the 2021 CEIP (i.e., energy
efficiency programs for multi-family split incentive between tenant and landlords,
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Chapter 6: Distributed Energy Resource Options
manufactured/mobile homes, single family weatherization and community and small
business, with the Community Identified Projects being addressed with the EAG RBA). A
few distinctions of the EAG's initiatives are callouts for those who are unhoused, tree
canopy, and emphasis for tribal partners — the latter is a component of Highly Impacted
Communities.
Avista continues to engage with and update the EAG on the progress of their identified
NCIF initiatives above. The Company also provides updates to other interested parties
through public participation meetings on spending, projects implemented, and the impact
to Named Communities through the NCIF. The NCIF administration and governance
includes an internal advisory group with representation from Avista's Energy Efficiency
department and other interested parties such as regulatory, external communications,
and the clean energy department to evaluate all NCIF awards for projects and programs.
In 2023, 21 projects were awarded or utilized NCIF funding totaling $1,382,129. This
included 10 energy efficiency projects, two distribution resiliency projects, five customer
or community grants, a pilot for medical battery back-up and outreach and engagement.
The energy efficiency projects funded in the report year included health and safety for
manufactured homes, efficiency upgrades at an affordable housing complex and homes
in an area devasted by the wildfire, a lighting project at a rural fairground, and energy
audits for the buildings located on tribal land. The information from the audits was used
to submit a resiliency grant to a state organization. This project, funded by the grant award
coupled with the NCIF, is expected to save approximately 340,000 kWh per year, while
saving over $30,000 in annual energy costs for the one building alone. The upgrades are
also expected to offset 3,091 pounds of CO2e by replacing aging equipment and
decommissioning outdated, high-emitting refrigerant.
In most cases, resiliency projects span multiple years. In 2023, NCIF committed to a
community center project that is expected to be completed in 2025. This project received
state funding along with an NCIF grant and is designed to help develop a neighborhood
resilience center to provide shelter and resources during climate and other emergencies.
As of June 2024, four awards were committed for workforce development, HVAC
replacements, tree plotter software for planned tree canopy and air conditioner
distribution to Avista electric customers were made, totaling $315,906. Avista will expand
outreach activities to raise awareness of NCIF to engage underrepresented groups in the
upcoming year.
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Chapter 6: Distributed Energy Resource Options
Other Company Initiatives
Spokane Tribe Partnership
Avista continues to partner with the Spokane Tribe of Indians to design a grid resiliency
solution in Wellpinit, Washington. This project is funded through a design grant from the
Department of Commerce Clean Energy Fund, with matching funds provided by Avista.
The goal is to develop an energy delivery platform to enhance grid resiliency for Wellpinit
and surrounding areas. The solution, termed a "resiliency station," is envisioned as a
modernized, centralized facility providing energy resiliency in Wellpinit through a
microgrid solution with an integrated battery energy storage system. The microgrid will be
a small-scale power system operating independently from the traditional grid to serve
critical loads when source power is interrupted, allowing vital support services to remain
functioning during outages, wildfire scenarios, and other natural disasters.
The resiliency station would create a "critical loads" circuit to prioritize power to three
buildings identified by the Tribe as critical to operations during emergencies. They include
the Spokane Tribal administrative building, the David C. Wynecoop Memorial Health
Clinic, and the Tribal Public Safety building. This station would replace some of the
existing stepdown infrastructure in Wellpinit, freeing up the area for future redevelopment
while improving the aesthetics and functionality of the distribution system. Based on
preliminary modeling, Avista estimates the resiliency station could leverage existing
generation resources, including solar and diesel generators, to sustain typical summer
building loads for all three buildings for up to seven days.
A site located in Wellpinit, along Agency Loop Road, has been identified as the preferred
project site. The approximately 0.72 acre site is large enough to house a battery energy
storage system, pad mount equipment, and a control enclosure for microgrid controls.
Station components will be securely enclosed to isolate critical electrical components
from the public, while simultaneously providing an innovative means to showcase the
facility, educate the public, and support the Spokane Tribe's long-term vision of energy
sovereignty.
Over the last few months, Avista has provided technical assistance to the Tribe as they
completed an application for $2.75 million from the Washington State Department of
Commerce Tribal Clean Energy grant fund towards construction of the resiliency station.
Total project costs are expected to be approximately $6.65 million. Avista and the
Spokane Tribe are committing to funding the balance of the project from a variety of
sources including Avista's NCIF and a U.S. Department of Energy Grid Resiliency
Formula Grant that has been awarded to the Spokane Tribe.
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Chapter 6: Distributed Energy Resource Options
Connected Communities
Avista partnered with Edo, Pacific Northwest National Labs (PNNL), and Urbanova to
create a business model to scale grid-enabled and efficient buildings to actively
participate in offsetting electric production and the delivery of demand resources as an
effort to elevate overloading a distribution feeder near its capacity. Edo, a business
partnership between McKinstry and Avista Development, is the prime recipient of the
Department of Energy's Connected Communities grant award. Edo represents the
scalable business model for creating "Active Demand and Energy Management" services.
Avista, a subrecipient in the grant award, is responsible for designing customer product
solutions to combine energy efficiency, residential smart thermostats, commercial
building energy optimization systems, managed EV charging, and residential battery
technology to be aggregated into a locational targeted virtual power plant. Avista will
operate "as an aggregator" to schedule, dispatch, and control the customer demand
products to address system balancing requirements at the supply and delivery systems.
The project will recruit 20-25 commercial participants and 50 to 100 residential
participants, with the goal of creating between 1 to 2.5 MW of flexible load. The utility will
administer "flex events" where Avista will adjust dispatchable assets such as smart
thermostats and residential batteries. Customers will retain the ability to "opt out" of flex
events by manually overriding event set points. Customers will receive varying incentive
payments depending on their level of participation.
Commercial and Industrial recruitment launched in the second quarter of 2024.
Residential and small and medium business customer recruitment will launch in the third
quarter of 2024. All participating customers must reside within the Third and Hatch
substation service boundary for the Connected Communities pilot project to help with
feeder capacity. The Third and Hatch substation has eight distribution feeders serving
four distinct neighborhoods. Most of these neighborhoods are in the City of Spokane
Opportunity Zone. Figure 6.6 outlines the timeline for the Connected Communities
program.
Figure 6.6: Connected Communities Timeline
PROJECT PILOT TESTING ANALYZE & REVIEW &
PI ONNING oSCFSSMFNT PHASF FVALUATF PIIRI ISH
Strategic planning and Enrollment of first Completion of Aggregation and Finalization of a business
design for delivering participants and testing enrollment and analysis examination of energy model playbook allowing
demand Flexibility and of planned energy of preliminary testing efficiency measures and for program replication
energy measures. measures from flex events grid service testing and management
2023 IS 2025 10 2025 • 2026 © 2027 IS
July January July • July July
------------ ------------ ------------ ------------ ------------
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Chapter 7: Supply-Side Resource Options
7. Supply-Side Resource Options
Avista evaluates several generation options including Distributed Energy Resources
(DERs) and utility-scale resource options to meet future resource deficits. This resource
plan evaluates upgrading existing resources, constructing utility-owned new generation
facilities, and contracting with other energy companies. This chapter describes the costs
and characteristics of the utility-scale resource options Avista is considering in the 2025
IRP. Most resource options are generic, as resources are typically acquired through
competitive processes such as a Request for Proposal (RFP). Due to siting, engineering
or financial requirements, this process may yield resources differing from this IRP in terms
of resource type, size, cost, and operating characteristics. It may also result in securing
output from existing resource options available in the region.
Section Highlights
• Future competitive acquisition processes may identify new or existing
resources using different technologies with differing costs, sizes, or
operating characteristics.
• The Inflation Reduction Act (IRA) tax incentives are included in resource
costs.
• Solar, wind, and other renewable resource options are modeled as Power
Purchase Agreements (PPA) instead of utility ownership.
• Avista models several energy storage options including pumped storage
hydro, lithium-ion and flow batteries, hydrogen, iron-oxide, and ammonia.
New Resource Options
Resource options in this analysis include those commercially available and future
resource technology options with a strong likelihood of commercial availability. The
analysis does not include theoretical options or technologies in pre-commercial phases,
nor does it consider variants of a technology, such as natural gas or wind plants made by
different manufacturers. A representative plant for each technology type was chosen.
Resource opportunities must be located within or near Avista's service territory with
verifiable costs and generation profiles priced as if Avista developed and owned the
generation or acquired generation from Independent Power Producers (IPPs) through a
PPA. Resources using PPAs rather than ownership include pumped hydro storage, wind,
solar (with and without storage), geothermal, and nuclear.
Resource options assuming utility ownership include natural gas-fired combined cycle
combustion turbines (CCCT), simple cycle combustion turbines (SCCT), natural gas-fired
reciprocating engines, ammonia- and renewable natural fueled gas-fired SCCTs, energy
storage, hydrogen fuel cell, biomass, and upgrades to existing facilities. New coal-fired
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Chapter 7: Supply-Side Resource Options
units were not included or considered. Modeling resources as PPAs or ownership does
not preclude the utility from acquiring new resources in other manners but serves as a
cost estimate for the new resources. Several other resource options described later in the
chapter are not included in the portfolio analysis but are discussed as potential resource
options as they may appear in a future RFP.
It is difficult to accurately model potential contractual arrangements with other energy
companies as an option in the plan, specifically for existing units or system power, but
such arrangements may offer a lower customer cost when a competitive acquisition
process is completed. Avista plans to use a competitive RFP process for resource
acquisitions where possible to ensure the lowest cost resource is acquired for customers.
However, other acquisition processes may yield better pricing on a case-by-case basis,
especially for existing resources available for shorter periods. Avista uses the IRP, RFPs,
and market intelligence to determine and validate its upgrade alternatives when
evaluating upgrades to existing facilities. Upgrades typically require competitive bidding
processes to secure contractors and equipment.
The costs of each resource option described in this chapter do not include the cost related
to upgrading the transmission or distribution system described in Chapter 8 or third-party
wheeling costs. All costs are considered on Avista's side of the interconnection point.
Avista excludes costs on the third-party side of the interconnection point to allow for
consistent cost comparison as resource costs are highly dependent on the location in
relation to Avista's system. These costs are included when Avista evaluates the resources
for selection in an RFP and within the IRP portfolio analysis. All costs are levelized by
discounting nominal cash flows by the 6.5% weighted average cost of capital approved
by the Idaho and Washington Commissions.66 All costs in this section are in 2026 nominal
dollars unless otherwise noted. All cost calculations and operating characteristic
assumptions for generic resources and PPA pricing calculations are available in Appendix
G and on Avista's website.67
Avista relies on several sources for resource costs including the National Renewable
Energy Laboratory (NREL)68, Northwest Power and Conservation Council (NPCC or
Council), publicly available energy consultant reports, press releases, regulatory filings,
internal analysis, other publicly available studies, developer estimates, as well as Avista's
experience with certain technologies to develop its generic resource assumptions. In
addition, Avista's 2022 All-Source RFP was utilized to ensure assumed costs for solar,
wind, combined solar and storage, and other resource options were in line with pricing
available from actual projects within or near Avista's service territory.
66 Idaho Order No. 35909 in Case No AVA-E-23-01, Washington Dockets UE-220053 Final Order 10/4.
67 www.myavista.com/about-us/integrated-resource-planning.
68 NREL (National Renewable Energy Laboratory). 2023. 2023 Annual Technology Baseline. Golden, CO:
National Renewable Energy Laboratory. Technologies I Electricity 12023 1 ATB I NREL
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Chapter 7: Supply-Side Resource Options
Levelized resource costs illustrate the differences between generator types. The values
reflect the cost of energy if the plants generate electricity during all available hours of the
year. Plants do not generally operate at their maximum generating potential because of
market and system conditions. Costs are separated between energy in $/MWh and
capacity in $/kW-year to better compare technologies.69 Without this separation of costs,
resources operating infrequently during peak-load periods would appear more expensive
than baseload CCCTs, even though peaking resources provide lower total cost when
operating only a few hours each year. Avista levelizes the cost using the production
capability of the resource. For example, a natural gas-fired turbine is available 92% to
95% of the time when accounting for maintenance and forced outages. Avista divides the
cost by the amount of megawatt hours the machine is available to produce energy and
not expected to operate. For generators limited by fuel availability, such as solar or wind,
resource costs are divided by its expected production.
Distributed Energy Resources
This IRP includes several DER options. DERs are both supply-and-demand-side
resources located at either the customer location or at a utility-controlled location on the
distribution system. Demand side DERs include energy efficiency and demand response
(DR), each are discussed in Chapter 6. Avista includes forecasts for customer-owned
solar and electric vehicles as part of its load forecast discussed in Chapter 3.
In addition to demand-side DERs, supply-side resource options include small scale solar
and battery storage. Avista includes specific cost estimates for smaller scale projects
described in Chapter 6 along with the energy, capacity, and ancillary service benefits
traditional utility scale projects offer. Any additional benefits due to project location, such
as improving line loss with DERs over alternative utility scale projects are also included.
Other locational benefits may be credited to the project if it alleviates distribution
constraints. Projects on the customer side may also provide reliability benefits to the
specific customer.
Natural Gas-Fired Combined Cycle Combustion Turbine
Natural gas-fired CCCT plants provide reliable capacity and energy for a relatively modest
capital investment. The main disadvantages of CCCT generation are cost volatility due to
reliance on natural gas (unless utilizing hedged fuel prices) and air emissions. This
analysis models CCCTs as a "one-on-one" (1x1) configuration with duct fire capability,
using hybrid air/water cooling technology and zero liquid discharge. The 1 x1 configuration
consists of a single gas turbine with a heat recovery steam generator (HRSG) and a duct
burner to gain more generation from the steam turbine. While larger size plants with
higher efficiencies are available such as 2x1 configuration, these are too large for Avista's
system without a partner. Avista prefers CCCT plants with nameplate capacity ratings
between 180 MW and 312 MW unless it is sharing the facility with other utilities.
69 Storage technologies use a $ per kWh rather than $ per kW because the resource is both energy and
capacity limited.
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Chapter 7: Supply-Side Resource Options
Cooling technology is a major cost driver for CCCTs. Depending on water availability,
lower-cost water cooling technology could be an option similar to Avista's Coyote Springs
2 plant. Without access to water rights, a more capital-intensive and less efficient air-
cooled technology is required. Avista assumes water is available for plant cooling based
on its internal analysis, but only enough water rights for a hybrid system utilizing the
benefits of combined evaporative and convective cooling technologies.
This analysis includes one CCCT plant option sized at 312 MW with 1x1 configuration
and duct fire capability. Avista reviewed several CCCT technologies and sizes and
selected this plant type as the best fit for the needs of Avista's customers for IRP planning.
If Avista were to pursue a new CCCT, a competitive acquisition process will allow analysis
of other CCCT technologies and sizes at both Avista's preferred and other locations. It is
also possible Avista could acquire an existing CCCT resource from one of the units in the
Pacific Northwest.
The most likely location for a new CCCT is in the Rathdrum, Idaho area, mainly due to
Idaho's lack of an excise tax on natural gas consumed for power generation, a lower sales
tax rate relative to Washington, and lack of state taxes or fees on carbon dioxide
emissions, such as Washington's Climate Commitment Act (CCA) unless imported into
the state of Washington.70 Likely CCCT sites would be on or near Avista's transmission
system to avoid third-party wheeling costs. Another advantage of siting a CCCT resource
in Avista's Idaho service territory is access to relatively low-cost natural gas on the Gas
Transmission Northwest (GTN) pipeline. Avista owns a site with these potential natural
gas connection points if it needs to add additional capacity from a CCCT or other
technology.
CCCT technology efficiency has improved since Avista's current CCCT generating fleet
entered service with heat rates as low as 6,400 Btu/kWh for a larger facility and 6,700 for
smaller configurations. Duct burners can add additional capacity with heat rates in the
7,200 to 8,400 Btu/kWh range.
The anticipated capital costs for the modeled CCCTs, located in Idaho on Avista's
transmission system with allowance for funds used during construction (AFUDC) on a
greenfield site, are approximately $1,422 per kW in 2026 dollars. These estimates
exclude the cost of transmission and interconnection. Table 7.1 details the levelized plant
cost assumptions, split between capacity and energy, for the combined cycle option
discussed here and the natural gas peaking resources discussed in the next section. The
costs include firm natural gas transportation, fixed and variable O&M, and transmission.
Table 7.2 summarizes key cost and operating components of natural gas-fired resource
options. Competition from alternative technologies and the need for additional flexibility
70 Washington state applies an excise tax on all fuel consumed for wholesale power generation, the same
as it does for retail natural gas service, at approximately 3.852%. Washington also has higher sales taxes
and carbon dioxide mitigation fees for new plants.
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Chapter 7: Supply-Side Resource Options
for intermittent resources are likely to put downward pressure on future CCCT costs.
Avista is not modeling carbon capture for natural gas facilities until proven technology can
be demonstrated.
Natural Gas-Fired Peakers
Peaking resources, such as natural gas-fired simple cycle combustion turbines (SCCT)
and reciprocating engines, provide low-cost capacity energy as needed. Technological
advances coupled with a simpler design relative to CCCTs allow SCCTs to start and ramp
quickly, providing regulation services and reserves for load following, and support for
variable energy resource integration.
This analysis models frame and reciprocating engine technologies; however, other
technologies would be considered in resource acquisition. Natural gas-fired peckers have
different load following abilities, costs, generating capabilities, and energy-conversion
efficiencies. Table 7.1 depicts the levelized cost for these technologies. Table 7.2 reflects
the cost and operational characteristics based on internal engineering estimates. This
analysis also considers using Renewable Natural Gas (RNG) as an alternative fuel in its
CT analysis or offsetting natural gas use with Renewable Thermal Certificates.
Firm natural gas fuel transportation is an electric generation reliability issue with FERC
and is also the subject of regional and extra-regional forums. For this plan, Avista includes
the cost of on-site fuel storage such as liquified natural gas (LNG) for all natural gas
turbine options within the capacity expansion model netted for the market arbitrage
benefit the assets create. Avista assumes non-firm gas transportation is available except
for short-term peak events requiring the use of on-site LNG storage. In addition to on-site
fuel storage, other options could be available for existing and new natural gas resources
to ensure plant availability for resource adequacy events, such as contracting for firm
natural gas transportation rights, purchasing an option to exercise the rights of another
firm natural gas transportation customer during peak demand times, or on-site fuel oil.
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Chapter 7: Supply-Side Resource Options
Table 7.1: Natural Gas-Fired Plant Levtmz_uu posts
Plant Name/Location A Total $1kW-Yr Variable Winter
7F .04 CT Frame Greenfield (Idaho) 62.0 107.1 49.4 180
7F .04 CT Frame Greenfield (Washington) 64.0 109.7 51.1
7F .04 CT Frame Greenfield + RNG (Idaho) 229.6 120.7 215.1 90
7F .04 CT Frame Greenfield + RNG (Washington) 229.9 123.3 215.1
Reciprocating Engine (ICE) Machine (Idaho) 64.3 160.3 45.4
Reciprocating Engine (ICE) Machine 185
(Washington) 66.2 164.2 46.6
NG CCCT (1x1 w/DF) (Idaho) 60.3 193.7 37.5 312
NG CCCT (1x1 w/DF) (Washington) 61.9 197.7 38.7
Tahle 7.2: Natural Gas-Fired Plant Cost and Operational Characteristics71
e/Location Capital Fixed Heat Variable Total Total
Cost with O&M Rate O&M Project Cost
7F .04 CT Frame Greenfield 929 168
(Idaho) 5.6 10,040 3.3 180
7F .04 CT Frame Greenfield 953 172
(Washington)
7F .04 CT Frame Greenfield + 929 168
RNG (Idaho)
7F .04 CT Frame Greenfield + 16.7 10,040 3.8 90
953 172
RNG (Washington)
Reciprocating Engine (ICE) 1,422 264
Machine (Idaho)
Reciprocating Engine (ICE) 5.6 8,190 6.9 185
1,459 271
Machine (Washington)
NG CCCT (1x1 w/DF) (Idaho) 1,422 443
NG CCCT (1x1 w/DF) 1,459 33.0 6,820 5.5 312 455
(Washington)
Wind Generation
Wind resources have no direct air emissions or fuel costs but are not dispatchable to meet
load. Avista models four general wind location options in this plan: Montana, Eastern
Washington, the Columbia River Basin, and offshore. Configurations of wind facilities are
changing given regional transmission limitations, federal tax credits, low construction
prices, and the potential for energy storage. These factors allow sites to be built with
" Costs based on Idaho. Washington's costs would be slightly higher due to a higher sales tax rate of 8.9%
compared with Idaho's 6.0% rate.
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higher capacity levels than the transmission system can currently integrate. When wind
facilities generate additional MWhs above the physical transmission limitations,72 the
generators typically feather (i.e., stop or reduce generation) or store energy using onsite
energy storage. At this time, Avista is not modeling wind with onsite storage or wind
facilities with greater output capabilities than can be integrated on the transmission
system. Avista's modeling process allows for storage to be sited at a wind facility if cost
effective.
Capital expenditures, including construction financing and O&M costs for onshore wind
with start dates from 2026 to 2045 can be found in Tables 7.3 and 7.4, respectively. Fixed
O&M does not include indirect charges to account for the inherent variation in wind
generation, often referred to as variable wind integration. The cost of wind integration
depends on the penetration and diversity of wind resources in Avista's balancing authority
and the market price of power.
Wind capacity factors in the Northwest range between 35% and 38% depending on
location and 42% to 52% range in Montana and offshore locations. This plan assumes
Northwest wind (Washington and Oregon) has a 35% average capacity factor, while
Montana and offshore wind have average capacity factors of 44% and 50%, respectively.
A statistical method, based on regional wind studies was used to derive a range of annual
capacity factors depending on the wind regime in each year (see Chapter 9, stochastic
modeling assumptions subsection for details).
Offshore wind has higher expected annual capacity factors (50%), but development and
operating costs are also much higher. At the time of this plan's analysis, developers have
not been offering an offshore product in the Pacific Northwest and are still in the early
stages of permitting and cost estimation.
Levelized wind costs change substantially due to the capacity factor but can also be
impacted even more by tax incentives and ownership structure. Table 7.5 shows the
nominal levelized prices with different start dates for each modeled location. These price
estimates assume a 20-year PPA with a flat pricing structure, including the cost of the
PPA, excise taxes, commission fees, and uncollectables73 to customers. These prices do
not include transmission costs for either capital investments or wheeling purchases nor
integration costs. If a wind PPA is selected in Avista's resource strategy, the model
assumes the PPA will extend through at least 2045.
72 If transmission is limited due to contractual reasons, an additional option is to buy non-firm transmission
to move the excess power.
73 Uncollectables refer to additional revenue collected from customers to cover the payments not received
from other customers.
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Photovoltaic Solar
Avista models solar system configurations as resource options. Utility scale options are
discussed here, while distributed systems under 5 MW located primarily on the customer
side of the meter, are discussed in Chapter 6. Utility-scale on-system solar facilities
assume a minimum capacity of 100 MW to take advantage of economies of scale and
single axis systems. There are also two generic locations for resource selection, the first
is local on-system resources within Avista's transmission system with a higher capacity
factor potential, and the second option is further south either in Oregon or Idaho and
requires transmission acquisition. Avista expects other locations to participate in future
RFPs. Tables 7.3 and 7.4 show capital and fixed O&M forecasts for these resources, and
the levelized prices for a 20-year PPA are detailed in Table 7.5. These costs do not
include transmission costs associated with new construction, wheeling purchases, or
integration costs.
T-hle 7.3: Forecasted Solar and Wind Capital Cost ($/kW)
2026 1,469 1,592 1,680 5,730
2030 1,382 1,573 1,711 5,888
2035 1,231 1,670 1,827 6,230
2040 1,266 1,768 1,947 6,677
2045 1,292 1,867 2,070 7,210
1 able 7.4: Forecasted Solar and Wind U&M (4i/Kw-yr.)
Year Utility Scale NW • Montana Off-Shore
Solar • • •
2026 23.97 31.33 33.75 100.22
2030 23.49 32.14 35.27 102.74
2035 22.63 34.67 38.02 107.85
2040 24.16 37.35 40.93 114.63
2045 25.74 40.19 44.00 122.81
Table 7.5: Levelized Solar and Wind Prices ($/MWh)
Off-ShoreW Utility Scale NW Wind Montana
Solar (On-System) Wind Wind M
2026 37.62 34.89 28.32 127.83
2030 28.37 28.73 23.86 125.54
2035 45.26 47.50 42.59 147.74
2040 46.37 63.33 58.44 169.46
2045 47.23 66.75 61.94 180.69
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Solar with Energy Storage (Lithium-ion Technology)
Solar paired with energy storage reduces costs attributable to sharing local infrastructure,
it can also directly shift energy deliveries, manage intermittent generation, use common
equipment, increase peak reliability, and can prevent energy oversupply by storing the
excess generation.
Lithium-ion technology prices are declining and will likely continue to fall due to increasing
manufacturing levels and product enhancements. Levelized costs for the three storage
sizes and durations modeled as solar PPAs based on a 100 MW solar facility are shown
in Table 7.6. Avista modeled 2- and 4-hour duration options. Avista's experience with
solar generation from its 19.2 MW Adams-Neilson PPA reveals significant energy
variation due to cloud cover and that on-site storage could be beneficial, but at this time
other resources can provide this service at a lower cost. For this analysis, Avista
considers the benefits for reducing the variable generation integration costs and
enhanced resource adequacy of the storage device within the resource selection model.
Currently, due to the complexity and range of potential storage configurations, the
analysis considers only the 2- and 4-hour designs. In addition, Avista's modeling of solar
plus storage allows the storage device to use grid power.
Table 7.6: Levelized Cost for Lithium-Ion Storage at a Solar Facility ($/kW-month)
Year 00 MWI 100
00 MWh 200 MWh 200 MWh
2026 15.18 10.17 6.25
2030 14.72 10.08 6.20
2035 17.88 12.15 7.25
2040 18.17 12.44 7.40
2045 18.34 12.67 7.51
Stand-Alone Energy Storage
Energy storage resources are gaining significant traction to meet short-term capacity
needs in the western U.S. Energy storage does not create energy but shifts it from one
period to another in exchange for a portion of the energy stored. Avista modeled several
energy storage options including pumped hydro, lithium-ion and flow batteries, and iron
oxide. In addition to the technological differences, Avista also considers different energy
storage durations for each technology. Pricing for energy storage is rapidly changing due
to technological advancements and the 2022 Inflation Reduction Act (IRA), providing tax
credits for all storage technologies through 2032.74 In addition to changing prices for
existing technologies, new technologies are entering the storage space with similar
characteristics and pricing as those modelled in this IRP such as battery systems using
74 The IRP does consider extension of the tax credits for safe-harbor construction where the tax credit can
be available for projects under construction in 2032, but not complete.
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sodium solid state technology. The rapid change in pricing and emergence of new
technologies justify the need to update prices and technology options for each IRP.
Another challenge with energy storage concerns pumped hydro technology where costs
and storage duration can be substantially different depending on the geography of the
proposed project. Energy storage is also gaining attention to address transmission and
distribution expansion, where the technology can alleviate conductor overloading and
short duration load demands rather than adding physical line/transmission capacity.
Please see Chapter 8 for more details about using storage as a non-wire alternative.
Energy storage cannot be shown in $ per MWh as with other generation resources
because storage does not create energy, but rather stores it and incurs losses. The
analysis shown in Figure 7.1 illustrates the cost differences between the technologies
when capital cost (2030 dollars) is divided by duration of storage but does not consider
the efficiency of the storage process or the pricing of the energy stored. This analysis is
performed in the resource selection process within modeling the resource operations
within Aurora.
Figure 7.1: Enerav Storage Upfront Capital Cost versus Duration
Pumped Hydro (8 hr)
Dist Scale Lithium-Ion (4 hr)
Dist Scale Lithium-Ion (8 hr)
Lithium-Ion (4 hr)
Lithium-Ion (8 hr)
Lithium-Ion (16 hr) •
Flow Battery (4 hr)
Pumped Hydro (16 hr)
Hydrogen Fuel Cell (40 hr)
Pumped Hydro (24 hr)
Flow Battery (8 hr)
Iron Oxide (100 hr) $32
Frame CT + Ammonia (350 hr) $4
$0 $100 $200 $300 $400 $500 $600 $700
$ M per Hour of Capacity
Pumped Hydro Storage
Pumped hydro is the most prolific energy storage technology currently used in both the
U.S. and internationally. This technology uses two or more water reservoirs at different
elevations. When prices or loads are low, water is pumped to a higher reservoir and then
released during periods of higher price or load. This technology may also help meet
system integration needs from intermittent generation resources. Only one of these
projects exists in the northwest and several more are in various stages of the permitting
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process. Advantages with pumped hydro include the technology's long service life and
Avista's familiarity with the technology as a hydro generating utility. The greatest
disadvantages are high capital costs and long permitting cycles.
Pumped hydro has good round trip efficiency rates; Avista assumes 80% for most options.
Projects are designed to utilize the amount of water storage in each reservoir and the
generating/pump turbines are sized for how long the capacity needs to operate. Avista
models this technology with three different durations including 8, 16, and 24 hours.
Durations are the number of hours the project can run at full capacity. Pricing and duration
of these facilities are based on projects currently being developed in the Northwest. As
an energy-limited water system, Avista includes different duration times to ensure
resources have sufficient energy to provide reliable power over an extended period in
addition to meeting single hour peaks. The complete range in levelized cost for pumped
hydro is shown in Table 7.7. Options also include a $0.54 per MWh variable payment for
each MWh generated (2021 base year, escalating with inflation).
Table 7.7: Pumned Hvdro Options Cost ($/kW-month)
2026 25.37 23.01 21.47
2030 27.70 25.12 23.45
2035 30.91 28.04 26.17
2040 55.45 50.11 46.62
2045 61.89 55.93 52.04
Lithium-Ion Batteries
Lithium-ion technology is one of the fastest growing segments of the energy storage
space. This section focuses on energy storage as a stand-alone resource rather than
coupled with solar as discussed earlier. For modeling purposes, lithium-ion assumes
utility ownership, but it could be acquired through a PPA for a 20-year life with
augmentation of the battery cells. Fixed O&M costs include replacement cells to maintain
80% energy conversion efficiency and capacity for this storage option. Estimated costs
include 2022 IRA federal tax credits.
Lithium-ion technology is an advanced battery using ionized lithium atoms in the anode
to separate their electrons. This technology can carry high voltages in small spaces
making it a preferred technology for mobile devices, power tools, and electric vehicles.
The large manufacturing sector of the technology is driving prices lower allowing the
construction of utility scale projects. Avista expects lithium-ion technology to evolve over
the planning horizon and new elements may be used to augment or replace lithium-ion.
Future IRPs will identify any advancement in battery technology.
Avista modeled five stand-alone configurations for lithium-ion batteries. Two DER small-
scale sizes (<5 MW) with 4- and 8-hour durations for modeling the potential for use on
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the distribution system and three larger systems (25 MW+), including 4- and 8-hour
durations, as well as a theoretical 16-hour configuration. Modeling assumptions for these
scenarios were derived from publicly available energy consultant sources. Figure 7.2
shows the capital cost forecast for each configuration of size and duration considered.
Avista classifies the 4-hour battery as the standard technology with capital and fixed O&M
costs in 2026 of $1,663 per kW and $41.57 per kW-year, respectively.
rigure 7.2: Lithium-ion Capital Cost Forecast
6,000
5,000
4,000
3,000
a
2,000
1,000 Utility Scale 16 hr Utility Scale 8 hr Utility Scale 4 hr
Dist Scale 8 hr Dist Scale 4 hr
0
CO f,- 00 M O N M ;I- LO Cfl � 00 M CDN CO � Cn
NNNNM M M M M M M M M M � It It � �
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Storage technology is often displayed differently than other resources to illustrate the cost
since it is not a traditional capacity resource. Table 7.8 shows the levelized cost per kW-
month for each configuration. This calculation reflects the levelized cost for the capital,
O&M, and regulatory fees, including capital reinvestments, over 20 years divided by the
capacity. These costs do not consider any variable costs, such as energy purchases.
Table 7.8: Lithium-Ion Levelized Cost ($/kW-month)
Year Jrility Scale Utility Scale Utility Scale
.4 hour 8 hour 16 hour
2026 13.25 23.61 44.33
2030 12.73 22.29 41.41
2035 19.41 33.79 62.55
2040 19.82 1 34.23 63.05
2045 20.07 34.35 62.93
Flow BatterieF
This plan models flow batteries with 4-hour and 8-hour duration in 25 MW increments.
Flow batteries have the advantage over lithium-ion because they do not degrade over
time which leads to a longer operating life. The technology consists of two tanks of liquid
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Chapter 7: Supply-Side Resource Options
solutions flowing adjacent to each other through a membrane to generate electrons
moving back and forth for charging and discharging.
Flow battery capital costs in 2026 are $1 ,317 and $1,383 per kW for the 4-hour and 8-
hour duration batteries, respectively, both falling 10% by 2035. Fixed O&M costs of
$71.52 and $80.46 per kW-year increase with inflation. Flow batteries have round-trip
efficiencies between 67% and 70%. Given Avista's recent experience with flow batteries
at its pilot project in Pulman, Washington, these efficiency rates are highly dependent on
the battery's state of charge and how quickly the system is charged or discharged. Table
7.9 shows the levelized cost per kW-month of capacity.
Iron Oxide Storage
Another new storage technology is an iron oxide battery where energy is stored using
energy created through the oxidization process. Iron is less expensive and more readily
available than lithium-ion or other storage technology elements. This technology uses
oxygen inside the battery to convert iron to rust and later convert it back to iron. Due to
the low cost of iron relative to other elements, a long-duration resource can be obtained
at similar cost compared to what is currently available, shorter duration technologies.
This analysis assumes a 100 MW iron-oxide battery with a 36.5% round-trip efficiency
with 100 hours, or 10,000 MWh, of storage. Capital costs are estimated at $3,037 per kW
(2026 dollars) and increase due to inflation. The fixed O&M cost of $27.90 per kW-year
and levelized cost of iron oxide storage is $248.04 per kW-year ($20.67 per kW-month)
for iron oxide storage, increasing with inflation in future periods. The actual costs are
uncertain given this resource is relatively new for commercial energy use.
1 able 7.9: storage Levelized cost ($kW-month)
I-Year Flow Battery F ow Batte IronOxide
4-hourab
II
2026 15.01 16.31 20.67
2030 15.26 16.62 21.06
2035 20.46 22.15 33.66
2040 21.45 23.27 34.33
2045 22.54 24.50 35.05
Renewable Green Hydrogen
The use of green hydrogen in the energy sector has been considered as a perennial
option for the distant future. This technology allows long-duration energy storage with the
potential to store enough power to continuously run for several days. Hydrogen can be
delivered by pipeline, truck, or rail and stored in tanks or underground caverns before
being converted back to power using a fuel cell or hydrogen-fueled turbine. The ability to
store hydrogen in tanks similar to liquid air means medium term durations can be
obtained. Significant research and development (R&D) dedicated to green hydrogen
technologies in transportation and other sectors may result in reduced costs or increased
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Chapter 7: Supply-Side Resource Options
operating efficiency. Transportation and other sectors could possibly utilize the electric
power system to create a cleaner form of hydrogen to offset gasoline, diesel, propane, or
natural gas.
Most hydrogen today uses methane-reforming techniques to remove hydrogen from
natural gas or coal. This technology is primarily used in the oil and natural gas industries
but, absent carbon sequestration, results may produce similar levels of greenhouse gas
emissions (GHG) from the combustion of the underlying fuels. If hydrogen is obtained
from clean energy through either electrolysis of water,75 pyrolysis,76 or even mined, the
amount of associated GHG emissions can be greatly reduced and therefor considered
green hydrogen. If renewable energy prices are low, the operating cost of creating green
hydrogen could also fall if hydrogen producers have access to power with low wholesale
electricity prices; however, capital costs would remain steady without significant
technology enhancements.
Converting hydrogen back into power could be done with a hydrogen fuel cell or directly
in a combustion turbine similar to natural gas-fired generation. Figure 7.3 shows the
forecasted delivered price (nominal) of green hydrogen to a potential fuel facility in
Avista's service territory". The development and delivery of green hydrogen is estimated
based on the projected cost of electrolyzer technology with reduction in costs expected
due to scaling and access to low-cost renewable electric power and water.
Figure 7.3: Wholesale Green Hydrogen Costs per Kilogram
4.50
4.00
3.50
E 3.00
L �
c 2.50 -
Y 2.00
L
d _ �
a 1.50 -
1.00
0.50
0.00
CO rl- co 6) O N co 'T LD CO rl_ 00 6) O N CO U')
N N N N M M Cl) M M Cl) Cl) M Cl) Cl) N �t I It
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
75 Current estimates require 2-3 gallons of water to create 1 kilogram of hydrogen.
76 Involves cracking natural gas into hydrogen and carbon black using electricity from clean resources.
77 1 kg of hydrogen is equivalent to 0.12 mmbtu natural gas or if hydrogen is$3.86 per kg is equal to$32.17
per mmbtu of natural gas equivalent.
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Chapter 7: Supply-Side Resource Options
The second step in the hydrogen fuel concept is to convert the hydrogen back to power.
For this conversion, a fuel cell would be assembled for utility scale needs (Avista uses 25
MW increments for this resource). The estimated capital cost for a fuel cell is $7,095 per
kW with a forty-hour storage vessel plus fixed O&M at $200 per kW-year (2026 dollars).
Table 7.10 shows the all-in levelized cost of hydrogen including both the fuel cell capital
recovery fixed cost and the fuel cost per MWh. Avista chose to use a fuel cell for hydrogen
fuel rather than a CT to provide an emission free resource and due to likely limitations of
storing the quantity of fuel required to operate a CT.
There are significant safety concerns relative to hydrogen to be resolved and mitigated
as hydrogen fuel ignites more easily than gasoline or natural gas. Adequate ventilation
and leak detection are important elements in the design of a safe hydrogen storage
system. Hydrogen burns with a nearly invisible flame which requires special flame
detectors. Some metals become brittle when exposed to hydrogen, so selecting the
appropriate metal is important to the design of a safe storage system. Finally, appropriate
training in hydrogen handling would be necessary to ensure safe use. Appropriate
engineering along with safety controls and guidelines could mitigate the safety risks of
hydrogen but would add to the high capital and operating costs of this resource option.
Another option to generate power with hydrogen is to use it in a CT, currently co-firing is
possible at Avista's Coyote Springs 2 and Rathdrum units if adequate cost-effective
hydrogen supplies are available. While this is a viable option, Avista also considers an
ammonia turbine to address storage and safety concerns with hydrogen.
Ammoni
An alternative resource option to hydrogen is clean ammonia.'$ Ammonia could be
sourced from the same process as green hydrogen, but ammonia requires an additional
step by adding nitrogen using the Haber-Bosch process. Current estimates, considering
the hydrogen electrolysis process, estimate the round-trip efficiency of this technology
with a CT for power production at 13%'79 although with technology improvements the
round-trip efficiency may reach 20%. The advantage of ammonia as a fuel over hydrogen
is its ability to be stored in larger volumes in an aqueous form and transported in larger
quantities at a lower cost. Hydrogen storage in large quantities requires large geologic
storage and this is not known to exist near Avista's service area.
For this resource option, two 90 MW capacity combustion turbines (180 MW) using a
common 30,000 metric ton storage tank could hold 55,812 MWh hours of energy storage,
enough to generate power for 310 consecutive hours at full capacity. Ammonia storage
78 Using ammonia as a fuel is clean from a GHG perspective but burning it emits NOx as part of the
combustion process. Manufacturers are currently working on SCR controls for ammonia fuel related NOx
emissions, in the meantime, Avista assumes 0.015 Ibs per mmbtu of combustion for this emission.
79 This assumes one metric ton of ammonia requires 13.9 MWh of power from the upstream processes
including electrolysis, desalination, pressure swing absorber, storage, and synthesis loops. Sagel,
Rouwenhorst, Faria, Green ammonia enables sustainable energy production in small island developing
states: A case study on the island of Curacao, 2022.
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Chapter 7: Supply-Side Resource Options
tanks are commonly used in the agricultural industry for fertilizer and modified natural gas
turbines capable of ammonia combustion are actively being developed by turbine
manufactures. Another advantage of this technology is the creation of green ammonia for
use in agriculture. This secondary use can help offset the investment cost and risk to a
utility by partnering with other industries needing ammonia.
Avista estimates ammonia gas turbine capital costs at $1,079 per kW (2026 dollars) and
is expected to increase with inflation due to the use of mature technology. In 2026, fixed
O&M costs are$16.74 per kW-year and carry a $3.75 per MWh variable charge in addition
to the cost of the ammonia. The forecasted price of ammonia is based on the hydrogen
price forecast shown in Figure 7.3 adjusted for conversion and transportation costs. As
ammonia will be created from clean electric generation, the pricing of the hydrogen
includes the associated power, water, and power delivery costs. The resulting Ievelized
fixed and operating cost are shown in Table 7.10.
Table 7.10: Hvdroaen Based Resource Oation Costs
ear Fixecd • . . •
• . �i
2026 89.52 131.42 12.84 215.12
2030 97.75 103.95 14.02 234.38
2035 109.10 82.92 15.64 260.92
2040 121.77 63.70 17.46 290.49
2045 135.92 46.02 19.49 323.40
Wooay tsiomass Generation
Woody biomass generation projects use waste wood from lumber mills or forest
management and are considered renewable and clean resources. In the biomass
generation process, a turbine converts boiler-created steam into electricity. A substantial
amount of wood fuel is required for utility-scale levels of generation. Avista's 50 MW Kettle
Falls Generation Station consumes more than 350,000 tons of wood waste annually or
about 48 semi-truck loads of wood chips per day. It typically takes 1 .5 tons of wood to
make one megawatt-hour of electricity, but this varies with the moisture content and
quality of the fuel. The viability of another Avista biomass project depends on the long-
term availability, transportation needs, and cost of the fuel supply. Unlike wind or solar,
woody biomass can be stockpiled and stored for later use. Many announced biomass
projects fail due to not being able to secure a reliable long-term fuel source.
Based on market analysis of fuel supply and the expected use of biomass facilities, a new
facility could be a wood-fired "peaker". The capital cost for this type of facility would be
$5,308 per kW in addition to the $32.09 per kW-year and $4.13 per MWh of fixed and
variable O&M costs (2026 dollars). The Ievelized cost is $649.18 per kW-year ($54.10
per kW-month) for a 2026 project plus fuel and variable O&M costs. Avista modeled two
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Chapter 7: Supply-Side Resource Options
methods of creating new biomass power for this IRP's analysis: the first is to upgrade the
existing Kettle Falls facility by 10 MW and the second is to add a second unit to the facility.
Geothermal Generation
Geothermal energy provides predictable capacity and energy with minimal GHG
emissions (zero to 200 pounds per MWh). Some forms of geothermal technology extract
steam from underground sources to run through power turbines on the surface while
others utilize an available hot water source to power an Organic Rankine Cycle
installation. Due to the geologic conditions of Avista's service territory, no geothermal
projects are likely to develop locally. Geothermal energy often struggles to compete
economically due to high development costs stemming from having to drill several holes
thousands of feet below the earth's crust with no guarantee of reaching geothermal
resources. Ongoing geothermal costs are low, but the capital required for locating and
proving viable sites is significant. The cost estimate for a future geothermal PPA is $57.90
per MWh in 2026 at Avista's transmission interconnection point.
Nuclear
Avista includes nuclear power as a non-emitting fuel resource option by modeling small
modular reactors (SMRs). Given the uncertainty of their economics, regional political
issues with the technology, U.S. nuclear waste handling policies, and Avista's modest
needs relative to the size of modern nuclear plants, Avista will have challenges
developing a nuclear project. In addition, a project may require partnerships with other
utilities in the Western Interconnect who want to incorporate nuclear power into their
resource mix and offer Avista a PPA.
The viability of nuclear power is changing as national policy priorities focus attention on
decarbonizing the nation's energy supply. The limited amount of recent nuclear
construction experience in the U.S. makes estimating construction costs difficult. Cost
projections rely on industry studies, recent nuclear plant license proposals, and the small
number of recently completed projects. SMR designs could increase the potential for
additional nuclear generation by shortening the permitting and construction phase and
making these traditionally large projects (over 1,000 MWs) a better fit for smaller utilities.
Given this possibility, Avista included an option for small scale nuclear power in the IRP
analysis. The estimated cost for nuclear per MWh on a levelized basis in 2030 is $143.76
per MWh assuming capital costs of$8,224 per kW (2026 dollars) as a PPA.
Other Generation Resource Options
Resources not specifically included as options in this analysis include cogeneration,
landfill gas, anaerobic digesters, and central heating districts. This plan does not model
these resource options explicitly, but continues to monitor their availability, cost, and
operating characteristics to determine if the technologies become economically viable
with any changes in state or federal incentives.
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Chapter 7: Supply-Side Resource Options
Exclusion from the analysis does not automatically exclude non-modeled technologies
from Avista's future resource portfolio. The non-modeled resources can still compete with
resources identified in the resource strategy through competitive acquisition processes
when the Company solicits resources to fill known resource needs. Competitive
acquisition processes can identify cost effective technologies to displace resources in the
resource strategy. Another possibility includes acquisition through a Public Utility
Regulatory Policies Act (PURPA) contract. PURPA allows developers to sell qualifying
power to Avista at set prices and terms80 outside of an RFP process.
Landfill Gas Generation
Landfill gas projects generally use reciprocating engines to burn methane collected at
landfills. The costs of a landfill gas project depend on the site specifics. The Spokane
area had a project at one of its landfills, but it was retired after the fuel source fell to an
unsustainable level. Much of the Spokane area uses the Spokane Waste to Energy Plant
instead of landfills for solid waste disposal. Using publicly available costs and the
Northwest Power and Conservation Council (NPCC) estimates, landfill gas resources are
economically promising, but are limited in their size, quantity, and location. Many landfills
consider cleaning the landfill methane to create pipeline quality gas due to low wholesale
electric market prices. This form of RNG has become an option for natural gas utilities to
offer a renewable gas alternative to customers. The duration of this form of gas supply
depends on the on-going disposal of trash, otherwise the methane could be depleted in
six to nine years.
Anaerobic Digesters (Manure or Wastewater Treatment)
Plants with anaerobic digesters typically capture methane from agricultural waste, such
as manure or plant residuals, and burn the gas in reciprocating engines to power
generators or directly inject clean fuel into natural gas pipelines as RNG. These facilities
tend to be significantly smaller than most utility-scale generation projects at less than five
megawatts. Most digester facilities are at large dairy and cattle feedlots, but like landfill
gas, many developers are opting to inject the gas into natural gas pipelines as RNG to
achieve higher returns on their investment.
Wastewater treatment facilities can host anaerobic digesting technology. Digesters
installed when a facility is initially constructed help the economics of a project significantly,
although costs range greatly depending on system configuration. Retrofits to existing
wastewater treatment facilities are possible but tend to have higher costs. Many of these
projects offset energy use at the facility so there may be little, if any, surplus generation
capability. Avista currently has a 260-kW wastewater digester system under a net
metered PURPA contract with a Spokane County wastewater facility.
80 PURPA rates, terms, and conditions are available at www.avistautilities.com under Schedule 62.
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Chapter 7: Supply-Side Resource Options
Small Cogeneration
Avista has few industrial customers with loads large enough to economically support a
cogeneration project. If an interested customer developed a small cogeneration project,
it could provide benefits including reduced transmission and distribution losses, shared
fuel, capital, and emissions control costs, as well as credit toward Washington's EIA
efficiency targets.
Another potentially promising option is natural gas pipeline cogeneration. This technology
uses waste-heat from large natural gas pipeline compressor stations. Few compressor
stations exist in Avista's service territory, but the existing compressors in the Company's
service territory have potential for using this generation technology. A big challenge in
developing any new cogeneration project is aligning the needs of the industrial facility
with the utility need for power. The optimal time to add cogeneration is during
development or retrofit of an industrial process, but the retrofit may not occur when the
utility needs new capacity. Another challenge to cogeneration is estimating costs when
such costs are driven by host operations. The best method for the utility to acquire this
technology is likely through PURPA or through a future RFP.
Coal
New coal-fired plants are extremely unlikely due to current policies, emission performance
standards, and the shortage of utility scale carbon capture and storage projects. The risks
associated with future carbon legislation and projected low natural gas and renewables
costs make investments in this technology highly unlikely. It is possible in the future there
will be permanent carbon capture and sequestration technology at price points to
compete with alternative fuels. Avista will continue to monitor this development for future
IRPs.
Heating Districts
Historically, heating districts were preferred options to heat population dense city centers.
This concept relies on a central facility to either create steam or hot water to distribute to
buildings via a pipeline for end use space and water heating. Avista provided steam for
downtown Spokane using a coal-fired steam plant, a concept still used in many cities and
college campuses in the U.S. and Europe but using natural gas as a fuel source. Creating
new heating districts necessitates suitable conditions, collaborative partners, and a
forward-thinking approach, much like the developments seen in Spokane's University
District.
Bonneville Power Administration
For many years, Avista received power from the Bonneville Power Administration (BPA)
through a long-term contract as part of the settlement from Washington Nuclear Project
Number 3 (WNP-3). Most of the BPA's power is sold to preference customers or in the
short-term market. Avista does not have access to power held for preference customers
but engages BPA on the short-term market. Avista has two other options for procuring
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Chapter 7: Supply-Side Resource Options
BPA power. The first is using BPA's New Resource rate. BPA's power tariff outlines a
process for utilities to acquire power from BPA using this rate for one year at a time. Since
this offering is short-term and variable priced, Avista does not consider it a viable long-
term option for planning purposes; however, it is a viable alternative for short-run capacity
needs. The other option to acquire power from BPA is to solicit an offer. BPA is willing to
provide prices for periods when it has excess power or capacity. This process would likely
parallel an RFP process for future capacity needs and likely take place after the current
BPA agreements with public power customers ends in 2027. Purchasing power from BPA
is advantageous as it's counted as nearly carbon free and can be used for compliance
with Washington's Clean Energy Transformation Act (CETA) legislation and the CCA, but
this benefit may result in a premium cost.
Existing Resources Owned by Others
Avista has purchased long-term energy and capacity from regional generation,
specifically the Public Utility Districts in the Mid-Columbia region, Columbia Basin Hydro's
irrigation projects, and a tolling agreement for the Lancaster Generating Station. Avista
contracts are discussed in Chapter 4, but extensions or new agreements could be signed.
If utilities are long on capacity, it is possible to develop agreements to increase Avista's
capacity position. Since these potential agreements are based on existing assets, prices
depend on future markets and may not be cost-based. Avista could acquire or contract
for energy and capacity of existing facilities without long-term agreements. The Company
anticipates these resources will be offered into future RFPs and may replace any selected
resources.
Upgrade Opportunities
Avista has investigated opportunities to add capacity at existing facilities for the last
several IRPs and implementing these projects if and when cost effective. The potential
project upgrade opportunities for this IRP are outlined below.
Rathdrum CT
There are two options to upgrade the existing Rathdrum CT. The first is to uprate the
combustion and turbine components at the Rathdrum CT, as the firing temperature can
increase to 2,055 degrees from 2,020 degrees providing a 5 MW increase in output. The
second project would install a new inlet evaporation system that could increase the
Rathdrum CT capacity by 10 MW on a peak summer day, but no additional energy is
expected during winter months.
Existing PPA Renewals and/or Repowering
Avista has three renewable energy PPAs expiring within the current IRP time horizon.
The analysis includes the opportunity to repower facilities or renew the PPA at prices
reflective of similar project pricing. For Palouse wind, the PPA is assumed to be able to
be repowered to 120 MW in 2043. Although the Rattlesnake Flat Wind PPA does not
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Chapter 7: Supply-Side Resource Options
assume a repower option due to transmission limitations, it is eligible for renewal in 2041.
Adams-Neilson Solar remains at 20 MWs with a renewal option in 2039.
Qualifying Capacity Credits (QCC)
In order to differentiate between resources' ability to meet peak load, QCCs are estimated
for both existing and new resources. QCCs are an estimate of the resources' ability to
meet peak load hours for resource adequacy. They are not the estimated generation
during the peak hour. QCCs are similar to Effective Load Carrying Capability (ELCC)
estimates. Avista uses QCCs to simplify detailed hourly modeling results when modeling
resources at a greater time granularity. Avista uses monthly time steps for capacity
expansion analysis and therefore a QCC is estimated for each resource type by each
month for each year. Table 7.11 is a summary of these QCC for winter (January) and
Summer (August).
Table 7.11: Qualifying Capacity Credit for Certain Resources
SUMEMMENi
Solar 3% 3% 3% 36% 24% 20%
NW Wind 6% 5% 4% 11% 10% 9%
Montana Wind 30% 27% 26% 20% 19% 18%
4 Hour Energy Storage 82% 56% 37% 74% 53% 40%
8 Hour Energy Storage 98% 83% 60% 98% 89% 76%
24 Hour Energy Storage 98% 92% 83% 98% 95% 90%
100 Hour Energy Storage 98% 98% 98% 98% 98% 98%
Demand Response (3 hour)81 62% 58% 50% 58% 54% 46%
Demand Response (6 hour) 124% 115% 99% 116% 108% 93%
Avista estimates the QCCs by utilizing estimates from two primary sources - the Western
Power Pool's (WPP) Western Resource Adequacy Program (WRAP) and the Resource
Adequacy in the Pacific Northwest (March 2019) study conducted by E3. Between the
two sources Avista estimates the current QCC value for each resource and how the QCC
may change over time given the region's forecasted generation capacity forecast (from
the electric market price forecast). The QCCs are designed to estimate the resources'
ability to meet regional demand as opposed to Avista's. The reason it estimates regional
demand is to use the same QCC value for complying with the WRAP for consistency
purposes and to simplify the process of estimating QCC values for each resource to save
substantial Avista staff time. To validate whether these regional QCC values also meets
Avista's resource adequacy requirements, Avista tests the resource portfolio using an
hourly model (ARAM) to ensure the portfolio meets Avista's resource adequacy metrics.
81 Avista did not have QCC values from either external study for demand response. To overcome this
deficiency Avista assumes demand response will receive 100% QCC if the program can deliver 6 hours of
load reduction, and if it is less then it will receive a proportionate amount. Further, Avista assumes DR is a
load reduction and therefore gets an additional credit to the QCC value to cover the avoided planning
reserve margin (PRM).
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Chapter 7: Supply-Side Resource Options
This is done by conducting a study of a future year(2030) load expectation and resources.
Placeholder natural gas CT resources are added to the system until the system's
reliability meets a 5% Loss of Load Probability (LOLP). Then using the total QCC in
megawatts of the existing resources and the placeholder resource and comparing it to
the expected peak load, Avista can estimate the PRM for planning purposes (i.e. 24% in
the winter). For further detail on resource adequacy modeling see Chapter 5.
Non-Energy Impacts
Washington's CETA requires investor-owned utilities to consider equity-related non-
energy impacts (NEIs) in integrated resource planning. Avista contracted with DNV for
the 2023 IRP to perform a NEI study on supply-side resources to 1) conduct a
jurisdictional scan to identify additional NEIs that were not specifically listed in Avista's
scope, 2) identify NEIs available through federal and regulatory publications, 3) develop
quantitative estimates on a $/MWh or $/kW basis as appropriate for each resource, and
4) conduct a gap analysis to provide recommendations to prioritize future research based
on the necessary level of effort or anticipated value.
DNV completed a supply-side NEI database and final report on April 8, 2022. Avista
includes NEIs using this study in the resource strategy analysis for the supply-side
resources modeled. This is in addition to the NEIs that had previously been included on
energy efficiency. These NEIs include the societal impacts of Avista's decision making
when selecting new resources and represent quantifiable values to prioritize resource
choices. By including these impacts, the analysis can prioritize resource decisions more
equitably. For example, resources with air emissions versus those without emissions are
evaluated to consider the environmental impact on local communities. The NEI values
used for this analysis are in Table 7.11.
There were areas with insufficient information for DNV to provide estimated NEI values
for any specific NEI types for specific supply-side resources. Where Avista did not have
a value from DNV, it estimated values by using approximation techniques. For many of
these areas, the research value and effort needed to address these gaps were significant.
Examples of some of these areas with insufficient information were related to public
health, safety, reliability and resiliency, energy security, environmental (wildfire, land use,
water use, wildlife, surface air effects), economic, and decommissioning relative to some
or all resource types (e.g., battery storage, hydrogen electrolyzer, etc.). Washington
directives indicate a movement to require NEIs in resource planning and research,
however quantifying these would require significant time and investment. It appears a
more cost-effective consistent approach would be best conducted at a state-wide level.
As part of an effort to continue to enhance the use of NEIs in the IRP Avista acquired the
IMPLAN model. IMPLAN is an economic model where the user inputs the direct impacts
of investments, and the model calculates the indirect and induced economic and
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Chapter 7: Supply-Side Resource Options
employment impacts of the investments. For example, the investment in a local wind
project has a direct investment in the equipment and employment used to develop the
project. The indirect effects are the impacts to the local economy of the related spending,
such as construction workers and spending money at local restaurants and hotels during
the development of the wind site. The induced effects are based on the multiplier process
in the local economy where the local recipients of the hypothetical wind project would
spend a portion of that money on local goods and services.
Avista used IMPLAN to estimate the economic effects to the local economy and then used
the results in the NEI portion of the IRP analysis. IMPLAN was used to model the impacts
of both capital spending and the operation of different types of resources. Avista also
considered the economic effects of plant construction by placing an economic benefit for
local generation resources compared to out-of-service area resources for selection in this
plan. Table 7.12 shows the resource NEI values used in developing the IRP. The negative
numbers indicated a benefit of the resource, and a positive value represents a cost. The
economic benefits include the value of induced and indirect economic growth from
operating the resource. Safety includes the estimated cost of potential injuries or deaths.
Public health includes costs related to air emissions other than GHG. Lastly, operating
jobs per MW is included as a reference point of the estimated long-term jobs created per
MW of the resource.
Table 7.12: IRP Resource NEI Values
OperatingResource Economic Safety Public
Benefits ($/MWh) Health . •
Solar(Washington) -0.71
0.23 N/A 0.02
Solar(Out of State) -0.30
Wind (Washington) -0.57
0.44 N/A 0.04
Wind (Out of State) -0 29
Natural Gas SCCT 5.28
Natural Gas CCCT -4.81 0.14 2.04 0.51
Power to Gas SCCT N/A
Storage -0.60 N/A N/A 0.25
Wood Biomass -4.69 0.19 14.85 0.32
Small Modular Nuclear Reactor -0.50 0.13 N/A 0.60
Pumped Hydro -0.37 0.30 N/A 0.07
Hydrogen Fuel Cell -4.81 0.14 N/A 0.51
Geothermal -3.20 0.14 N/A 0.53
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Chapter 8: Transmission and Distribution Planning
8. Transmission & Distribution Planning
This chapter introduces Avista's Transmission and Distribution (T&D) systems, provides
a brief description of how Avista studies these systems, and recommends capital
investments to maintain reliability while accommodating future growth. Avista's
Transmission System is only one part of the networked Western Interconnection with
specific regional planning requirements and regulations. This chapter summarizes
planned transmission projects and generation interconnection requests currently under
study and provides links to documents describing these studies in more detail. This
chapter also describes how distribution planning is incorporated into the Integrated
Resource Plan (IRP) and Avista's merchant transmissions system rights.
Section Highlights
• Transmission Planning estimates costs of locating new generation on
Avista's system for the IRP.
• Avista formed a Distribution Planning Advisory Group (DPAG) for
additional involvement of interested parties, education, and transparency.
• Avista's cluster study process for new generation connects includes 26
projects, including wind, solar, energy storage, natural gas, biomass, and
hydro.
Avista Transmission System
Avista owns and operates a system of over 2,200 miles of electric transmission facilities
including approximately 700 miles of 230 kV transmission lines and 1,600 miles of 115
kV transmission lines (see Figure 8.1).
Figure 8.1: Avista Transmission System
Kettle Falls
Colville
Sandpoint
Clark Fork
Chelan _ "Noxon
,wa-thdrum
Coeur lene Thompson Falls
pokane
Kellogg
Othello Moscow
Pullman
Clarkston Lewiston
115 kV
Grangeville 230kV
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Chapter 8: Transmission and Distribution Planning
230 kV Transmission System
The backbone of Avista's Transmission System operates at 230 W. Figure 8.2 shows a
station-level depiction of Avista's 230 kV Transmission System including network
interconnections to neighboring utilities and relevant path boundaries. Avista's 230 kV
Transmission System is interconnected to Bonneville Power Administration's (BPA) 500
kV transmission system at the Bell, Hatwai, and Hot Springs substations. In addition to
providing enhanced transmission system reliability, network interconnections serve as
points of receipt for power from generating facilities outside Avista's service area. These
interconnections provide for the interchange of power with entities within and outside the
Pacific Northwest, including integration of long- and short-term contract resources.
Figure 8.2: Avista 230 kV Transmission System
---- South of Boundary- -----FJ
655 MW l T
a
176 W 1 ---178 Bell
---- --r--
-- BPA '
1 '
' VN Lancaster Noxon Rapids '
1 it BPA AVA '
' z18 MW 71e 2 w Hot Springs
Grand Coulee ' ----------- ---------- - -------
------------
f
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BPA ' 1 0 MW 799 W 1 w Beacon w z
1 AVA
Cabinet Gorge
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AVA
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AVA ' AVA 3 z9e MW Idaho-Northwest(Path 14L J
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1 . - - - - - - - - - - - - - - - - - - - - - !
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Chapter 8: Transmission and Distribution Planning
Transmission Planning Requirements and Processes
Avista coordinates transmission planning activities with neighboring interconnected
transmission owners. Avista complies with Federal Energy Regulatory Commission
(FERC) requirements related to both regional and local area transmission planning. This
section describes several of the processes and forums important to Avista's transmission
planning.
Western Electricity Coordinating Council
The Western Electricity Coordinating Council (WECC) is responsible for promoting bulk
electric system reliability, compliance monitoring and enforcement in the Western
Interconnection. This group facilitates the development of reliability standards and
coordinates interconnected system operation and planning among its membership.
WECC is the largest geographic territory of the regional entities with delegated authority
from the National Electric Reliability Council (NERC) and the FERC. It covers all or parts
of 14 Western states, the provinces of Alberta and British Columbia, and the northern
section of Baja, Mexico.82 See Figure 8.3 for the map of NERC Interconnections including
WECC.
RC West
California Independent System Operator's (CAISO) Reliability Coordinator (RC) West
performs the federally mandated reliability coordination function for a portion of the
Western Interconnection. While each transmission operator within the Western
Interconnection operates its respective transmission system, RC West has the authority
to direct specific actions to maintain reliable operation of the overall transmission grid.
Western Power Pool
Avista is a member of the Western Power Pool (WPP)83, an organization formed in 1942
when the federal government directed utilities to coordinate river and hydro operations to
support war-time production. The WPP serves as a northwest electricity reliability forum,
helping to coordinate present and future industry restructuring, promoting member
cooperation to achieve reliable system operation, coordinating power system planning,
and assisting the transmission planning process. WPP membership is voluntary and
includes the major generating utilities serving the Northwestern U.S., British Columbia,
and Alberta. The WPP operates several committees, including its Operating Committee,
the Reserve Sharing Group Committee, the Western Frequency Response Sharing
Group Committee, the Pacific Northwest Coordination Agreement (PNCA) Coordinating
Group, and the Transmission Planning Committee (TPC) and Avista participates in each.
82 NERC Interconnections.pdf
83 The organization was formally named the Northwest Power Pool.
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Chapter 8: Transmission and Distribution Planning
Figure 8.3: NERC Interconnection Map
Quebec
Interconnection
Interconnections
I �
I �
a�' I "
t Eastern
Western Interconnection / N Interconnection
/ N.
/ ERCOT
N.Interconnection
■MRO ■NPCC ❑RF ■SERC ❑Texas RE ■WECC
NorthernGrid
NorthernGrid formed on January 1, 2020, and includes membership from fourteen utility
organizations within the Northwest and many external parties. NorthernGrid aims to
enhance and improve the operational efficiency, reliability, and planned expansion of the
Pacific Northwest transmission grid. Consistent with FERC requirements issued in Orders
890 and 1000, NorthernGrid provides an open and transparent process to develop sub-
regional transmission plans, assess transmission alternatives (including non-wires
alternatives) and provide a decision-making forum and cost-allocation methodology for
new transmission projects. NorthernGrid is a new regional planning organization created
by combining the members of ColumbiaGrid and the Northern Tier Transmission Group.
System Planning Assessment
Development of Avista's annual System Planning Assessment (planning assessment)
encompasses the following processes, which can be found on Open Access Same-time
Information System (OASIS) at http://www.oatioasis.com/avat:
• Avista Local Transmission Planning Process — as provided in
Attachment K, Part III of Avista's Open Access Transmission Tariff
(GATT);
• NorthernGrid transmission planning process — as provided in the
NorthernGrid Planning Agreement; and
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Chapter 8: Transmission and Distribution Planning
• Requirements associated with the preparation of the annual planning
assessment of the Avista portion of the Bulk Electric System.
The planning assessment, or local planning report, is prepared as part of a two-year
process as defined in Avista's OATT Attachment K. The Planning Assessment identifies
the Transmission System facility additions required to reliably interconnect forecasted
generation resources, serve the forecasted loads of Avista's network customers and
native load customers, and meet all other transmission service and non-GATT
transmission service requirements, including rollover rights, over a 10-year planning
horizon. The planning assessment process is open to all interested parties, including, but
not limited to transmission customers, interconnection customers, and state authorities.
Additional information regarding Avista's system planning work is in the Transmission
Planning folder on Avista's OASIS site noted above. Avista's most recent transmission
planning document highlights several areas for additional transmission expansion work
including:
• Big Bend - Transmission system capacity and performance has
significantly improved with the completion of the Othello Substation
and an interconnecting 115 kV Transmission Line. These projects are
the last phase of the Saddle Mountain 230 kV system reinforcement
adding a fourth source into the load center. The addition of
communication, aided protection schemes, and other reconductor
projects improved reliability and reduced the impacts of system faults.
This project supports continued load growth in the area and integration
of utility scale renewable generation.
• Coeur d'Alene - The completion of the Coeur d'Alene - Pine Creek
115 kV Transmission Line rebuild project and Cabinet - Bronx - Sand
Creek 115 kV Transmission Line rebuild project improved
transmission system performance in northern Idaho. The addition and
expansion of distribution substations and a reinforced 115 kV
transmission system were needed in the near-term planning horizon
to support load growth and ensure reliable operations in this area.
• Lewiston/Clarkston - Load growth in the Lewiston/Clarkson area
contributes to heavily loaded distribution facilities. Additional
performance issues have been identified that impact the ability for bulk
power transfer on the 230 kV transmission system. A system
reinforcement project is under development to accommodate the load
growth in this area.
• Palouse - Completion of the Moscow 230 kV station rebuild project
added capacity and mitigated several performance issues. The
remaining issue is a potential outage of both the Moscow and
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Chapter 8: Transmission and Distribution Planning
Shawnee 230/115 kV transformers. An operational and strategic long-
term plan is under development to determine how to best address a
possible double transformer outage in this area.
• Spokane - Several performance issues exist in the Spokane area
transmission system, and they are expected to get worse with
additional load growth. The Westside 230 kV station capacity increase
and Sunset Substation rebuild are complete. The staged construction
of new facilities to support load growth in the West Plains is under
development with the Blue-Bird — Garden Springs 230 kV project. A
new 230 kV source into the greater Spokane area will offload the
Beacon station, improving system performance for outages related to
transmission lines terminating at the station.
Generation Interconnection
An essential part of the IRP is estimating transmission costs to integrate new generation
resources onto Avista's transmission system. A summary of proposed IRP generation
options along with a list of Large Generation Interconnection Requests (LGIR) are
discussed in the following sections. The proposed LGIR projects have independent
detailed studies and associated cost estimates and are listed below for reference.
IRP Generation Interconnection Options and Estimates
A summary of the generation interconnection location, size, and associated costs for new
and existing generation sites are listed in Tables 8.1 and 8.2 below. Further information
regarding each alternative can be found in the detailed integration study in Appendix E.
These studies provide a high-level view of generation integration, performance, and cost
estimates, and are similar to the system impact studies performed under Avista's
generator interconnection process. In the case of third-party generation interconnections,
FERC policy requires a sharing of costs between the interconnecting transmission system
and the interconnecting generator. Accordingly, Avista anticipates all identified generation
integration transmission costs will not be directly attributable to a new interconnected
generator.
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Chapter 8: Transmission and Distribution Planning
Table 8.1: New Generation Sites - Integration Cost MbL1111aLUs
• . • • POI Cost
VoltageArea of Integration (MW) Estimate
kL
Big Bend area near Lind (Tokio) 100/200 230 kV 127.8
Big Bend area near Odessa 100/200/300 230 kV 170.5
Big Bend area near Othello 100/200 230 kV 216.8
Big Bend area near Othello 300 230 kV 258.7
Big Bend area near Reardan 50 115 kV 9.7
Big Bend area near Reardan 100 115 kV 12.8
Lewiston/Clarkston area 100/200/300 230 kV 1.9
Lower Granite area 100/200/300 230 kV 2.9
Palouse area, near Benewah Tekoa 100/200 230 kV 2.4
Rathdrum Prairie, north Greensferry Rd 100 230 kV 34.0
Rathdrum Prairie, north Greensferr Rd 200/300/400 230 kV 53.9
Sandpoint Area 50 115 kV 1.6
Sandpoint Area 100/150 115 kV 48.2
West Plains area north of Airway Heights 100/200/300 230 kV 2.4
Table 8.2: Existing Generation Sites - Integration Cost Estimates
• . • •I) Station or Request POI Cost
Area of Integration (MW) Estimate
. .
AAK
Kettle Falls Station 50 115 kV 1.6
Kettle Falls Station 100 115 kV 19.0
Northeast Station 50 115 kV 1.6
Northeast Station 100 115 kV 7.7
Northeast Station 200 230 kV 25.9
Palouse Wind, at Thornton Station 100/200 230 kV 1.4
Rathdrum Station 25/50 115 kV 11.1
Rathdrum Station 100 230 kV 15.9
Rathdrum Station 200 230 kV 48.4
Large Generation Interconnection Requests
Third-party generation entities may request transmission studies to understand the cost
and timelines required for integrating potential new generation projects. These requests
follow a defined FERC process to estimate the system impacts, the facility requirements,
and cost estimates for project integration. After this process is completed, a contract to
integrate the generation interconnection project may occur and negotiations can begin to
enter into a transmission agreement, if necessary. Table 8.3 lists information associated
with potential third-party resource additions currently in Avista's interconnection queue.85
84 Cost estimates are in 2024 dollars and use engineering judgment with a 50% margin for error.
85 OAT OASIS.
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Chapter 8: Transmission and Distribution Planning
Table 8.3: Third-Party Large uuijuiation IIILt:9Ik;UIIIIt:9tAIUII RUydUbLb
FQ59 Solar/Storage Adams WA 60
Q60 Solar/Stora e Asotin WA 150
Q97 Solar/Storage Nez Perce ID 100
TCS-03 Solar/Storage Adams WA 80
TCS-14 Wind/Storage Garfield WA 375
CS23-06 Wind Whitman WA 256
CS23-12 Storage Franklin WA 199
CS23-13 Solar Lincoln WA 40
CS23-14 Solar Spokane WA 40
CS24-01 Solar Adams WA 1.1
CS24-02 Storage Spokane WA 0.5
CS24-03 Storage Adams WA 150
CS24-04 Storage Spokane WA 100
CS24-05 Natural Gas CT Kootenai ID 203
CS24-06 Natural Gas CT Bonner ID 120
CS24-07 Solar Adams WA 2
CS24-08 Solar/Storage Franklin WA 199
CS24-09 Solar Adams WA 9.5
CS24-10 Solar/Storage Spokane WA 80
CS24-11 Solar Whitman WA 70
CS24-12 Solar Whitman WA 40
CS24-13 Solar Whitman WA 95
CS24-14 Solar Spokane WA 40
CS24-15 Wind/Storage Lincoln WA 300
Future Transmission Projects Under Consideration
Blue Bird — Garden Springs 230 kV Project
Avista's system planning through the 10-year assessment planning horizon identified
transmission system needs for load growth across the south and west of Spokane.
Studies show system operability is strained and results in reduced system flexibility,
affecting safety, system resiliency, and ultimately service to Avista customers. Continued
load growth only amplifies this situation in the future.
The Blue Bird - Garden Springs 230 kV project was identified as the backbone piece of a
broader West Plains Transmission Reinforcement. The project's primary goal is to
develop a new and independent 230 kV source west of Spokane. The goal will be
addressed by sourcing 230 kV from BPA Bell - Coulee #5 230 kV Transmission Line to
improve contingency performance and increase system stability. The new 230 kV source
will provide the required reliability and operational flexibility to serve current and
forecasted loads.
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Chapter 8: Transmission and Distribution Planning
Increased transmission service capability is an additional benefit of developing a new and
independent 230 kV source west of Spokane. The location of this new 230 kV connection
is anticipated to increase power transfer capability between Avista and BPA by 10-30%
depending on the season.
North Plains Connector
This IRP considers a proposed regional transmission project to connect the Western
Interconnect with the Eastern Interconnect as a resource option. The project consists of
developing a 3,000 MW capacity direct current line between Colstrip, Montana, and North
Dakota with an on-line date of 2033. The end points in North Dakota would give Avista
access to both the Midcontinent Independent System Operator (MISO) and Southwest
Power Pool (SPP) markets to buy or sell power and provide access to generation
resources in the mid-continent with different weather patterns. This IRP evaluates this
resource as a 300 MW share utilizing the transmission path as a capacity only resource
limited by the qualifying capacity credit (QCC) from Montana located generation.
Colstrip Transmission System Upgrade
Avista and the other owners of the Colstrip Transmission System are evaluating upgrades
to the existing 500 kV transmission lines and supporting 230 kV and 115 kV infrastructure.
These upgrades would increase power transfers out of Montana by approximately 900
MW. The purpose of this study is to better identify the simultaneous increase in transfer
capability across the Montana to Northwest and West of Hatwai WECC rated paths.
Montana to Washington 500 kV transmission system upgrades were last studied by
NorthWestern, BPA, and Avista in May 2012, as part of the Colstrip to Mid-Columbia
Upgrade Project Study.
Lolo - Oxbow Upgrade and Optimization
Avista, as a prime recipient, in partnership with Idaho Power Company, is seeking grant
funding for their Lolo - Oxbow Transmission Upgrade and Optimization project. This
project will upgrade the Lolo - Oxbow 230 kV Transmission Line with high-capacity
conductors, as well as wildfire resilient designs and materials. Additionally, the project
includes integrating Idaho Power's new Pallette Junction Station and two SmartValve
technology deployments. These improvements will increase interregional transfer
capability by 450 MW between the Pacific Northwest and Mountain regions, presenting
an opportunity to increase the build of renewable energy resources in the region.
The Lolo - Oxbow Upgrade and Optimization project would bring innovative technologies
together resulting in improvements to interregional transfer capability by 450 MW from
Avista to Idaho and up to 185 MW in the opposite direction. The two innovative
technologies planned for this project are:
1) SmartValve technology opens the door to dynamically controlling and optimizing
power flows, and
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Chapter 8: Transmission and Distribution Planning
2) Infravision technology speeds transmission line construction with drone pull-line
stringing instead of helicopter use.
The local communities and region would benefit from capacity upgrades enabling future
generation interconnection opportunities to the Lolo - Oxbow 230 kV Transmission Line.
If awarded, there will be community benefit funding available for up to $3.3 million.
Additionally, through these upgrades, Avista will work towards further workforce
development in energy-supportive roles, such as on-site equipment training, special
operator training, and other job skill opportunities.
Distribution Resource Planning
Avista continually evaluates its distribution system for reliability, level of service, and
future capacity needs. The distribution system consists of about 380 feeders covering
30,000 square miles, ranging from three to 73 miles. Avista serves 414,000 electric
customers on its distribution grid.
The future of the distribution system is dynamic in terms of needs. Electric transportation,
all-electric buildings, behind the meter generation and storage, and data centers are
examples of modern disruptions to the distribution system. Understanding these
applications and predicting the system impacts is challenging.
Over the last several IRP cycles, Avista has continuously developed and improved its
processes and analytical abilities to allow distributed energy resources (DERs)to be fairly
evaluated for their stacked benefits as a resource and their impact to the distribution grid.
The growth of DERs on Avista's system has reached a point where incorporating DER
impacts into the upcoming planning assessment (2025) will provide actionable insights.
Overall, the existing impact of DERs on the distribution system has been minimal.
However, there are a few feeders approaching impactful levels of DER penetration (Table
8.4). The tools and confidence to analyze the future DER impacts has arrived just as the
uptake of DERs is becoming significant. In addition, the DER Potential Study provides
substantial pieces of missing data. These study results give Avista a reasonable estimate
of future DER penetration of where new generation or even electric vehicle load could
locate. The study is available in Appendix F.
As a point of reference, Idaho and Washington has about 4,500 generators and a total of
40 MW of installed generation on the distribution system. Total generation nameplate
capacity is greater while actual generation will be less. A majority of the generators are
net metered PV solar.
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Chapter 8: Transmission and Distribution Planning
Table 8.4: Existing uuiiviator k i uN 10 Ceedt.,,,
Total Feeder No.JJ Total No. Penetratiorr'
(kW) AL Lull"AL
TUR112 1,041 44 2,483 1.8
BKR12F1 794 83 2,481 3.3
GRA12F2 604 63 1,997 3.2
MIL12F3 495 57 2,173 2.6
FOR12F1 495 42 672 6.3
SUN12F2 477 61 2,154 2.8
F&C12F2 473 65 2,274 2.9
BLD12F4 473 45 1,991 2.3
LIB12F2 464 1 36 1 827 1 4.4
EFM12F1 457 1 44 1 1,461 1 3.0
Currently, Avista's third-party integration requests are few with only four small integrations
in the cluster study process ranging in size from 0.5 MW to 9.5 MW. The final disposition
of projects remains to be seen.
The above summarizes the existing state of resources on the distribution grid. As more
DER resources arrive in the future, the grid may become constrained. The extent of the
constraints, if any, will be revealed during the next system assessment as the measures
fitting the definition of DERs are hypothetically added to the system in future years based
on the DER Potential Study results.
Regardless of the cause of the grid constraint/deficiency (load growth, DER uptake, etc.),
a mitigation plan is needed. Mitigation projects may include "poles and wires" or possibly
another DER commonly referred to as non-wire alternatives. Where it makes financial
sense, non-wire alternatives have value such as the deferral of capital expenditures for
upgrading the system.
Deferred Distribution Capital Investment Considerations
New technologies such as energy storage, photovoltaics, and demand response
programs may help defer or eliminate capital investments to increase capacity of
distribution and transmission systems. This benefit depends on the new technologies'
ability to solve system constraints and meet customer expectations for reliability. An
advantage in using these technologies may be additional benefits incorporated into the
overall power system. For example, energy storage may help meet overall peak load
needs or provide voltage support on a particular distribution feeder or at a distribution
substation.
The analysis for determining the capital investment deferment value for DERs is not the
same for all locations on the system. Feeders differ by whether they are summer-peaking
or winter-peaking, the time of day when peaks occur, capacity thresholds, and the rate of
local load growth. It is not practical to have a deferment estimate for each feeder in an
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Chapter 8: Transmission and Distribution Planning
IRP, but it is helpful to have a representative estimate included in the IRP resource
selection analysis.
To fairly evaluate and select the most cost-effective solutions to mitigate system
deficiencies, the distribution planning process needs to identify the deficiency well in
advance of it becoming a performance issue. Longer evaluation periods provide enough
time for a comprehensive evaluation so the solution can take a holistic approach to
include system resource needs. A shorter period can lead to immediate action not lending
itself to a stacked value analysis due to time constraints for acquiring and/or constructing
a non-wire alternative.
Identifying future deficiencies in a timely manner is a focus of System Planning. As
previously mentioned, spatial forecasting, load data, time-series analysis, and accurate
modeling are critical to making decisions as early as possible. For the next system
assessment, Avista will use tools and data previously unavailable for the last assessment.
The additional results will help facilitate the evaluation of DERs as mitigation options for
any deficiencies identified.
Currently, Distribution Planning has not identified any projects meeting the criteria for an
economic non-wire alternative. The identified near-term distribution projects require
capacity increases and duration requirements exceeding reasonable DER capacity.
However, the process is maturing and will identify system needs further out in time
providing a longer runway needed to fully evaluate reasonable solutions including non-
wire alternatives.
Reliability Impact of Distributed Energy Storage
Utility-scale batteries may offer benefits to grid operations including, but not limited to,
reliability. This is particularly true in situations where the battery system is commissioned
as a mitigation solution on the distribution system.
There is an industry trend to broaden the list of remedies available to alleviate grid
deficiencies beyond traditional wires-based solutions. As discussed above, these
solutions are typically referred to as non-wire alternatives, but it may be more informative
to call them non-traditional alternatives. The motivation behind the trend is reasonable as
non-traditional approaches may be less expensive than legacy options and may also
incorporate other ancillary benefits, such as in the case of batteries. Utilities should
consider all viable options to arrive at a least cost and reliable solution to distribution
issues. In addition to solving grid issues, some non-wire alternatives may also serve as a
system supply resource. These alternatives are referred to as DERs. Batteries, the
subject of this section, are one such non-wire alternative with other benefits.
It is often presumed batteries increase system reliability. This may be true in some
applications, but in the narrow sense of non-wire alternatives, this would typically not be
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Chapter 8: Transmission and Distribution Planning
the case. In the simplest of terms, reliability can decrease with the addition of a battery
because the battery and its control system are additional failure points in the existing
system chain. It is difficult to identify a scenario where a reduction in reliability results from
adding potential failure points to a system.
A common issue on the distribution grid is feeder capacity constraints. A constrained
feeder typically approaches the operational constraint during the daily peak load. The
historical mitigation for this type of constraint is to increase the capacity of the constraining
element by installing a larger conductor, different regulators, a larger transformer, or
building a new substation. With the advent of utility-scale batteries, utilities have another
option to mitigate these types of feeder constraints.
When DERs are used to solve a delivery constraint in this manner, the battery or other
generating resource does not replace existing facilities, and this is a key point as the
probability of failure of the existing facilities remains. The probability of failure of the
battery or other non-wire alternative system is now an additional failure point. This is
analogous to a feeder as a chain where each link is a potential failure point. If the chain
consists of 100 links, there are 100 points of possible failure along the entire chain. In the
same manner, adding a battery to a feeder to mitigate an issue simply adds another link,
and another possible failure point in the chain. Instead of 100 possible points of failure,
there are now 101 possible points of failure. Granted there are temporal aspects to this
as well, but the battery will not always be a required solution to fix a constraint. If a failure
occurs in the battery when there is no constraint, the feeder can continue operating as
normal with no adverse impacts to the system. But there will be times when the battery is
needed to meet a local peak event and during those times the battery becomes an
additional failure point with the expanded system. The annual net effect on the feeder is
potentially reduced reliability especially as the reliability of current battery technology is
less than other traditional solutions.
The shift in reliability is more significant if a traditional solution was chosen. Existing older
links in the failure chain would be replaced with new, often more robust, and more reliable,
links. To take the chain analogy even further, if a new substation is built, links are removed
from the failure chain as each affected feeder becomes shorter and has less
environmental exposure. In addition, there is increased resiliency due to added
operational flexibility and the ability to serve load from different directions. The net effect
of a traditional solution is increased reliability, and it facilitates future DER resource
additions because traditional solutions allow the grid to more readily accept additional
DERs.
Quantifying the real effect of a grid-fixing battery or similar resource on reliability is difficult
and situational. Indeed, it may not rise to a level of concern given the temporal nature of
the decrease in reliability. The benefit of the resource may outweigh the short period of
time it increases failure probability. However, if the probability of failure increases
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Chapter 8: Transmission and Distribution Planning
significantly, an alternate solution may be warranted. From an IRP perspective, the notion
of solving a distribution grid deficiency while simultaneously providing a system resource
is intriguing and worthy of consideration, but system reliability improvements cannot
automatically be assumed with non-wire alternatives.
Electrification Impact Analysis
Avista's distribution system is not designed for a high penetration of electrification of
existing customer's transportation and space/water heating loads. Many studies including
this and past IRPs concentrate on the power supply and transmission requirements of
these new loads, but do not estimate additional distribution system costs. Traditionally,
distribution planning is outside the scope of an IRP as the IRP focuses on the generation
of the power supply not the delivery, but the cost to change the distribution system is
beneficial to understand the full impacts of a major transition policy decision for Avista's
customers.
This IRP contemplates four electrification scenarios for plausible Washington State load
changes within the IRP planning horizon (discussed in Chapter 10). The scenarios use
alternative forecasts for higher rates of electric vehicle (EV) adoption and a transition to
electric space and water heat of existing natural gas customers. Additional load
requirements by existing customers will have an impact on the distribution system as the
system was not designed for this additional load. The system changes and costs to
accommodate new loads will be a time-consuming exercise requiring assumptions for the
impacts of each individual customer for each of these scenarios. To shorten the
requirements for such a study, Avista chose to estimate the system impacts for the
highest load forecast scenario and base its estimate on high level assumptions for system
requirements based on known costs to construct system components. This analysis gives
an approximate estimate to add to the other power and transmission cost estimates
traditionally estimated in a resource plan.
There are two options to increase distribution capacity, one is to increase voltage of the
system; this option requires replacing all distribution underground cable, line insulation,
substation power transformers, voltage regulators, and numerous other equipment. The
second option is using the same distribution voltage to split the existing system up into
additional feeders by adding additional substations along with replacing targeted
conductors. For this analysis, the second option is used to estimate the system costs.
Avista estimated the required replacement components based on the judgement of
Avista's planning engineers and construction personnel. The high electrification scenario
adds 930 MW of additional winter peak load by 2045, but for system planning purposes
this is increased to 1,100 MW to account for higher loads due to the power supply
planning metric based on a 1-in-2 weather event and the distribution system must plan
for lower temperature events at 1-in-10 year lowest daily temperature. To account for new
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Chapter 8: Transmission and Distribution Planning
transmission and distribution costs in these high load forecasts equates to $287 per kW
of winter peak load on a levelized basis.
Distribution Planning Advisory Group Update
Avista formed the Distribution Planning Advisory Group (DPAG) following the 2021 Clean
Energy Implementation Plan (CEIP). There have been five 2-hour long meetings covering
various distribution topics including:
• March 2023: Power Delivery 101, Avista's Distribution System
Overview
• June 2023: Performance Criteria, Planning Basics, System
Assessment
• December 2023: System Needs, Solutions, DER Potential Study
Update
• March 2024: DER Potential Study Results
• July 2024: Interconnection Process, Hosting Capacity Maps, DER
Potential Assessment Maps
• December 2024: Weather dependent load modeling
The meetings have been well attended and the engagement is slowly ramping up as
comfort level increases. The results of the next system assessment should provide for
interesting and collaborative discussions with DPAG members. The previous assessment
was already well underway when the group formed so going through the next assessment
should be more fruitful for those attending.
Merchant Transmission Rights
Avista has two types of transmission rights—those owned by Avista and those purchased
from third parties. The first type includes Avista-owned transmission which is reserved
and purchased by Avista's merchant department to serve its customers. This type of
transmission is also available to other utilities and power producers. FERC separates
utility functions between merchant and transmission functions to ensure fair access to
Avista's transmission system. The merchant department dispatches and controls Avista's
generation and purchases transmission from the Avista transmission operator to ensure
that energy can be delivered to customers. Avista must show a load serving need to
reserve Network Transmission on the Avista-owned transmission system to ensure
equitable access to the transmission capacity. Appendix J shows the projected need and
future use of Avista's owned transmission system.
Avista also purchases transmission rights from other utilities to serve customers as listed
in Table 8.5 below. This transmission is procured on behalf of the merchant side of Avista.
The merchant group has transmission rights with BPA, Portland General Electric (PGE),
and a few smaller local electric utilities.
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Chapter 8: Transmission and Distribution Planning
Table 8.5: Merchant Tranbimbbiun Rights
Quantity
BPA Lancaster to John Day 100 6/30/2026
BPA Coyote Springs 2 to Hatwai 97 8/1/2026
BPA Coyote Springs 2 to Benton 50 8/1/2026
BPA Garrison to Hatwai 196 8/1/2026
BPA Coyote Springs 2 to Vantage 125 10/31/2027
BPA Coyote Springs 2 to Vantage 50 7/30/2026
BPA Townsend to Garrison 210 9/30/2027
PGE John Day to COB 100 12/31/2028
Northern Lights Dover to Sagle As needed n/a
Kootenai Electric Rockford to Worley As needed 12/31/2028
NorthWestern Clearwater to AVA-System 100 9/1/2029
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Chapter 9: Market Analysis
9. Market Analysis
A fundamental energy market analysis is an important consideration to support Avista's
resource strategy over the next 20 years. Avista uses forecasts of future market
conditions of the Western Interconnect to optimize its resource portfolio options. Electric
price forecasts are used to evaluate the net operating margin of each supply-side
resource and demand-side resource, including distributed energy resources (DER)
options, for comparative analysis between each resource type. The model tests each
resource in the wholesale marketplace to understand its profitability, dispatch, fuel costs,
emissions, curtailment, and other operating characteristics.
Section Highlights
• Solar and wind dominate future generation across the West, while natural
gas and increasing amounts of storage will ensure resource adequacy as
existing coal and older natural gas plants retire or reduce dispatch.
• By 2045, this study assumes 94% of generation in the Pacific Northwest
will be carbon free, compared to approximately 70-80% today (depending
on hydro condition).
• Greenhouse gas emissions (GHG) will fall to historic lows with the
expansion of renewables and continued coal and natural gas plant
retirements. By 2045, expected emissions will be 62% less than 1990.
• The 20-year wholesale electric price forecast (2024-2045) is $44.14 per
MWh, including costs from the Climate Commitment Act (CCA).
Expansion of renewables reduces future mid-day prices, but evening and
nighttime prices will be at a premium compared to today's pricing.
• Natural gas prices continue to remain low; for example, the levelized price
at Stanfield (2024-2045) is $3.61 per dekatherm.
Background
Avista conducts its wholesale market analysis using the Aurora model by Energy
Exemplar. The model includes generation resources, load estimates and transmission
links within the Western Interconnect. This chapter outlines the modeling assumptions
and methodologies for this Integrated Resource Plan (IRP) and includes Aurora's primary
function of electric market pricing (Mid-Columbia for Avista), as well as operating results
from the analysis. The expected case is an average of 300 simulations of future outcomes
using the assumptions on policies, regulations, and resource costs considered with the
Technical Advisory Group JAC).
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Chapter 9: Market Analysis
Electric Marketplace
Avista simulates the entire Western Interconnect electric system for its IRP; shown as
Western Electricity Coordinating Council (WECC)86 in Figure 9.1 . The rest of the U.S. and
Canada operate in separate electrical systems. The Western Interconnect includes the
U.S. system west of the Rocky Mountains plus two Canadian provinces and the northwest
corner of Mexico's Baja peninsula.
Figure 9.1: NERC Interconnection Map
QUEBEC
NERC INTERCONNECTIONS INTERCONNECTION
N-I
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WECC
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WESTERN
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INTERCONNECTION
The Aurora market simulation model represents each operating hour between 2026 and
2045. It simulates both load and generation dispatch for 19 regional areas or zones within
the west. Avista's load and most of its generation was in the Northwest zone, but to better
model the impacts of the CCA, Avista added granularity in the zones identified in Table
9.1. Each of these zones includes connections to other zones via transmission paths or
links. These links allow generation trading between zones and reflect operational
constraints of the underlying system, but do not model the physics of the system as a
power flow model. Avista focuses on the economic modeling capabilities of the Aurora
platform to understand resource dispatch and market pricing effects resulting in a
wholesale electric market price forecast for the Northwest zone or Mid-Columbia
marketplace. For this analysis, Avista modeled a Mid-Columbia marketplace both with
and without the impacts of the CCA.
S6 WECC is the Western Electrical Coordinating Council. It coordinates reliability for the Western
Interconnect.
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Chapter 9: Market Analysis
Table 9.1: Aurora Zones
Avista Southern Idaho
Bonneville Power Administration Oregon
Eastern Montana Washington
Northern California Wyoming
Central California Utah
Southern California Arizona
Colorado New Mexico
British Columbia Alberta
North Nevada Baja Mexico
South Nevada
The Aurora model estimates its electric prices using an hourly dispatch algorithm to match
the load in each zone with the available generating resources. Resource dispatch
considers fuel availability, fuel cost, operations and maintenance costs, dispatch
incentives/disincentives, and operating constraints. The marginal cost of the last
generating resource needed to meet area load becomes the electric price. The IRP uses
these prices to value each resource option (both supply and load side) and selects
resources to achieve a least reasonable cost plan meeting all load and reliability
obligations. Avista also conducts stochastic analyses for its price forecasting, where
certain assumptions are drawn from 300 distributions of potential inputs. For example,
each stochastic forecast randomly draws from an equally weighted probability distribution
of the 30-year rolling hydro record.
The following sections of this chapter discuss the assumptions used to derive the
wholesale electric price forecast, resulting dispatch, and greenhouse gas emissions
profiles of the west for the 300 stochastic studies.
Western Interconnect Loads
Each of the 19 zones in Aurora requires hourly load data for all 20 years of the forecast
plus 300 different stochastic studies for weather variation. Future loads may not resemble
past loads from an hourly shape point of view due to the continual increase in electric
vehicles (EVs) and rooftop solar. Changes in energy efficiency, demand curtailment/
demand response, varying state policies, population migration, and economic activity
increase the complexity. While each of these drivers are important to the power price
forecast, it takes a large volume of analytical time to estimate and track these macro
effects over the region. Avista uses the following methods to derive its regional load
forecast for power price modeling to account for these complexities.
Avista begins with Energy Exemplar's demand forecast included with the Aurora software
package. This forecast includes an hourly load shape for each region along with annual
changes to both peak and energy values. Avista updates the load forecast using a
national consultant's expectations on future loads. This base forecast is represented as
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Chapter 9: Market Analysis
the black dashed line in Figure 9.2. The WECC load grows 0.49% per year. Avista adjusts
this initial forecast to account for changes in EV penetration and net-metered generation,
including rooftop solar. Annual EV load grows at 12.4% and net-metered generation
grows at 8.7%.$' These adjustments increase the load forecast growth rate to
approximately 1.0% per year. Within the year, the hourly load shapes adjust to reflect
charging patterns of both residential and commercial vehicles in addition to most net-
metered generation being modeled as fixed roof mount solar panels.
Figure 9.2: 20-Year Annual Average Western Interconnect Load Forecast
140,000
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Base Load w/NetMeter Generation
20,000 Net Load Forecast
Base Load w/PH EV Load
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Regional Load Variation
Several factors drive load variability. The greatest short-run variability driver is weather.
Long-run economic conditions, like the Great Recession, tend to have a larger impact on
the load forecast. The load forecast increases on average at the levels in Figure 9.2, but
risk analyses emulate varying weather conditions and base load impacts.
Avista continues its previous practice of modeling load variation using Federal Energy
Regulatory Commission (FERC) Form 714 load data from 2018 to 2022. To maintain
consistent west coast weather patterns, statistically significant correlation factors
between the Northwest and other Western Interconnect load areas represent how
electricity demand changes together across the system. This method avoids
oversimplifying Western Interconnect loads. Absent the use of correlations, stochastic
models may offset changes in one variable with changes in another, virtually eliminating
$'Avista uses forecasts provided by a national consulting firm to assist in the development of these
forecasts.
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Chapter 9: Market Analysis
the possibility of broader load excursions witnessed by the electricity grid. The additional
accuracy from modeling loads this way is crucial for understanding wholesale electricity
market price variation, as well as the value and use of peaking resources in meeting
system variation.
Tables 9.2 and 9.3 present load correlations for this IRP. Statistics are relative to the
Northwest load area (Oregon, Washington and Idaho). "NotSig" indicates no statistically
valid correlation existed in the data. "Mix" indicates the relationship was not consistent
across the 2018 to 2022 period. For regions and periods with NotSig and Mix results,
the IRP does not model correlations between the regions. Tables 9.4 and 9.5 provide
the coefficient of determination values by zone.$$
i dole 9.2: idnuary LIIUUU911 june Load Area Correlations
Alberta Mix Mix 24% Not Sig 21% Not Sig
Arizona Mix 17% Mix Not Sig Mix 8%
BPA 72% Mix 73% 67% 18% 71%
British Columbia 79% 84% 76% 73% Not Sig 89%
CA-Northern 8% 10% Mix Not Sig Mix 9%
CA-Southern 8% 10% Mix Not Sig Mix 9%
Colorado Mix Mix Mix Mix Mix Mix
Idaho South 73% 65% 87% Not Sig Mix 38%
Montana 81% 86% 79% 41% Mix 47%
Nevada 8% 8% Not Sig Not Sig Mix 18%
New Mexico Mix Not Sig Mix Mix Mix Mix
Oregon 72% 75% 62% 67% 8% 77%
Utah 37% 76% 69% 27% Mix 38%
Washington 1 83% 1 90% 1 78% 1 78% 8% 84%
Wyoming I Not Sig 1 36% 1 53% 1 Not Sig 27% Mix
88 The coefficient of determination is the standard deviation divided by the average.
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Chapter 9: Market Analysis
Table 9.3: July through December Load Area Correlations
Area Jul Aug Sep Oct Nov Dec
Alberta Not Sig Mix Not Sig 41% Mix Not Sig
Arizona Mix Mix Mix -53% Not Sig 18%
BPA 70% 74% 62% Mix 77% 77%
British Columbia 85% 69% Not Sig 71% 76% 81%
CA-Northern 25% 27% Mix -55% 1 Not Sig Not Sig
CA-Southern 25% 27% Mix -55% Not Sig Not Sig
Colorado Mix Mix Mix Not Sig Mix Mix
Idaho South 19% 47% 44% 49% 73% 19%
Montana 75% 82% 76% 90% 86% 91%
Nevada 28% 26% Mix -43% 51% 38%
New Mexico Mix Mix Not Sig Not Sig 77% 17%
Oregon 79% 60% 39% 17% 77% 80%
Utah 71% 48% 41% 35% 77% 77%
Washington 83% 76% 64% 81% 87% 83%
Wyoming Not Sig 8% 8% Mix 70% 56%
Table 9.4: Area Load Coefficient of Determination (Standard Deviatforinvlean)
Area Jan Feb Mar Apr May Jun
Alberta 5.5% 8.1% 6.8% 6.1% 4.8% 8.3%
Arizona 5.5% 8.1% 6.8% 6.1% 5.7% 10.0%
BPA 4.9% 5.5% 5.5% 7.0% 8.1% 10.0%
British Columbia 5.1% 5.3% 5.7% 7.5% 6.9% 9.3%
CA-Northern 5.1% 1 5.3% 4.5% 5.7% 3.3% 4.7%
CA-Southern 5.3% 5.6% 5.3% 5.7% 3.3% 4.7%
Colorado 4.7% 5.9% 6.2% 7.0% 10.0% 12.6%
Idaho South 4.4% 6.1% 5.8% 5.1% 3.4% 5.0%
Montana 4.4% 6.1% 5.8% 5.1% 3.4% 7.0%
Nevada 3.2% 4.7% 4.6% 4.0% 3.3% 7.0%
New Mexico 4.1% 1 5.7% 5.1% 4.2% 1 5.0% 8.8%
Oregon 4.1% 5.7% 4.2% 5.3% 7.6% 9.0%
Utah 4.3% 5.6% 3.9% 5.3% 7.6% 9.0%
Washington 5.1% 5.3% 3.4% 8.2% 8.8% 8.7%
Wyoming 3.6% 4.9% 5.0% 4.3% 5.5% 7.4%
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Chapter 9: Market Analysis
Table 9.5: Area Load Coefficient of Determination (Standard Deviation/Mean)
OctArea Jul Aug Sep Dec
Alberta 8.3% 9.0% 5.9% 6.6% 6.7% 6.9%
Arizona 7.6% 7.8% 10.5% 7.8% 5.2% 5.0%
BPA 7.6% 7.8% 10.5% 8.5% 5.2% 5.2%
British Columbia 9.2% 9.1% 11.7% 9.7% 5.2% 5.2%
CA-Northern 5.2% 1 5.0% 3.3% 5.3% 1 4.9% 5.8%
CA-Southern 5.2% 7.3% 13.0% 5.0% 6.8% 5.8%
Colorado 6.0% 8.1% 13.0% 5.0% 6.8% 5.8%
Idaho South 6.0% 7.3% 4.7% 6.2% 5.0% 5.4%
Montana 5.2% 4.8% 7.2% 4.3% 4.2% 4.2%
Nevada 5.2% 4.8% 7.2% 4.4% 4.6% 4.8%
New Mexico 6.8% 5.9% 8.7% 4.8% 4.6% 4.8%
Oregon 6.3% 6.3% 8.4% 6.4% 4.0% 4.4%
Utah 6.3% 6.5% 10.1% 9.6% 3.8% 5.1%
Washington 8.9% 6.7% 10.1% 9.6% 3.8% 5.1%
Wyoming 5.1% 5.9% 7.5% 4.2% 4.9% 4.7%
Generation Resources
The Aurora model needs a forecast of generation resources to compare and dispatch
against the load forecast for each hour. A generation availability forecast includes the
following components:
• Resources currently available or known upgrades;
• Resources retiring or converting to a new fuel source;
• New resources for capacity and load service;
• New resources for renewable energy compliance; and
• Fuel prices, fuel availability and operating availability.
Aurora contains a database of existing generating resources with the location, size and
estimated operating characteristics for each resource. When a resource has a publicly
scheduled retirement date, or is part of an approved provincial phase-out plan, it is retired
for modeling purposes on the expected date. Avista does not project retirements beyond
those with publicly stated retirement dates or phase out plans. Less economical plants
operate fewer hours in the forecast. Several coal plant retirements have already or are
expected to occur in the Northwest during this IRP; these include Boardman, Colstrip
Units 1 and 2, North Valmy, and Centralia. Figure 9.3 shows the total retirements included
in the electric price forecast. Approximately 16,500 MW of coal, 9,600 MW of natural gas,
2,500 MW of nuclear, and 1,600 MW of other Western Interconnect resources including
biomass, hydro, and geothermal are known to be retiring by the end of 2045.
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Chapter 9: Market Analysis
Figure 9.3: Cumulative Resource Retirement ForetodbL
35,000
■Coal -Natural Gas ■Nuclear Hydro ■Other
30,000
25,000 -
20,000
cn 15,000
a _ —
10,000
5,000
0
�f1 tD I� 00 O O N M 0 to r-- W O O N M "I U1
N N N N N N M M M M M M M M M M � � � � � �
O O O O O O O O CI CI Co Co Co Co Co Co O O O O O O
N N N N N N N N N N N N N N N N N N N N N N
New Resource Additions
Considering state clean energy goals and the replacement of retired generation, a new
generation forecast must include enough resources to meet future peak loads.
Furthermore, some states include greenhouse gas (GHG) emission constraints or require
GHG emission pricing or offsets for new resource additions. Avista uses a resource
adequacy-based forecast for new resource additions along with data estimates provided
by a third-party consultant. The process begins with a forecast of new generation by
resource type from a national third-party consultant. Consultants with multiple clients and
dedicated staff can, more efficiently research new resource costs and operating
characteristics on likely resource construction in the West, especially in areas where
Avista has no market presence or local market knowledge. These forecasts for new
generation account for environmental policies and localized cost analysis of resource
choices to develop a practical new resource forecast.
The last step runs the model for 300 simulations to see if each load area can meet a
resource adequacy test. The goal is for each area to serve all load in at least 285 of the
300 iterations, with a 95% loss-of-load threshold measuring reliability.
Figure 9.4 shows the 324 GW of added generation included in this forecast. The added
resources include 112 GW of utility-scale solar, 93 GW of wind, 5 GW of natural gas
Combined Cycle Combustion Turbines (CTs), 67 MW of energy storage, 8 GW of natural
gas CTs, and 39 GW of other resources including hydro, biomass, geothermal, and net-
metering.
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Chapter 9: Market Analysis
Figure 9.4: Western Generation Resource Additions (Nameplate Capacity)
350
323.7
300
264.5
250
197.2
200
R
150 125.4
100
50
0 2030 2035 2040 2045
■H2CCCT 0.3 0.3 1.5 3.1
■H2CT 0.0 0.0 0.0 0.0
OSWind 1.5 8.3 15.2 23.9
■CCCT 4.9 4.9 5.4 5.4
SCCT 5.7 7.0 7.5 7.5
DR 5.1 5.3 5.5 5.8
■Storage 19.1 38.1 58.0 66.8
Net-Meter 9.1 13.5 16.8 20.8
Solar 47.6 73.4 92.6 112.0
■Wind 28.8 41.1 55.1 69.2
■Geothermal 1.8 2.8 4.1 6.0
■Biomass 0.2 0.4 0.5 0.7
Hydro 1.3 1.5 1.8 2.1
Generation Operating Characteristics
Several changes are made to the resources available to serve future loads to account for
Avista's specific expectations, such as fuel prices, and to reflect variation of resource
supply such as for wind and hydro generation.
Natural Gas Prices
Historically, natural gas prices were the greatest indicator of electric market price
forecasts. Between 2003 and 2023 the correlation between natural gas and on-peak Mid-
Columbia electric prices was 0.80, indicating a sizable decrease in correlation between
the two prices than historically observed. Natural gas-fired generation facilities were
typically the marginal resource in the northwest, except for times when hydro generation
was high due to water flow. In addition, natural gas-fired generation met 34% of the load
in the U.S. Western Interconnect in 2023. With the large increases in solar and wind
Avista Corp 2025 Electric IRP 233

Chapter 9: Market Analysis
generation in the west expected to continue, the number of hours where natural gas-fired
facilities will set the marginal market price is expected to decline.
For modeling purposes, Avista uses a baseline of monthly natural gas prices and varying
prices based on a distribution for each of the 300 stochastic forecasts. The forecasts
begin with the Henry Hub forecast. Since Avista is not equipped with fundamental
forecasting tools, nor is it able to track natural gas market dynamics across North America
and the world, it uses a blend of market forward prices as of 12/15/2023, consultant
forecasts, and the Energy Information Administration's (EIA) forecast. The EIA forecast
is compared in Figure 9.5 against forecasted Henry Hub prices from two consultants with
the capability to follow the fundamental supply and demand changes of the industry. The
20-year nominal Ievelized price of natural gas is $4.86 per dekatherm.89
Figure 9.5: 2025 IRP Henry Hub Natural Gas Price Forecast
$10.00
—IRP Forecast —Consultant 2
$9.00 Consultant 1 —EIAIAEO
_NYMEX
$8.00
$7.00
E $6.00
a
$5.00
Y
0 $4.00 0
0 r
Q 6
$3.00 N ov �D °�° e, Fsr
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(D I-- co o) O N M Un CO r­ CO O O N M V LO
N N N N M M M M M M M M M M Nr It V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Natural gas generation facilities in the West do not use Henry Hub as a fuel source, but
natural gas contracts are priced based on the Henry Hub index using a basin differential.
Northwest basins include Sumas for coastal plants on the William's Northwest pipe
system. Power plants on the Gas Transmission Northwest (GTN) pipeline obtain fuel at
prices based on AECO, Stanfield, or Malin depending on contracted delivery rights. Table
9.6 shows these basin differentials as a percent change from Henry Hub for the
deterministic case. This table also includes basin nominal Ievelized prices for 20 years
for the selected basins.
89 The natural gas pricing data is available on the IRP website within Appendix F.
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Chapter 9: Market Analysis
As described earlier, natural gas prices are a significant predictor of electric prices. Due
to this significance, the IRP analysis studies prices described on a stochastic basis for
the 300 iterations. The methodology to change prices uses an autocorrelation algorithm
allowing prices to experience excursions, but to not move randomly. The methodology
works by focusing on the monthly change in prices. The forecast's month-to-month
expected case price change is used as the mean of a lognormal distribution; then for the
stochastic studies, a monthly change in natural gas price is drawn from the distribution.
The lognormal distribution shape and variability uses historical monthly volatility. Using
the lognormal distribution allows for the large upper price excursions seen in the historical
dataset.
Table 9.6: Natural Gas Price Basin Differentials from Henry Hub
Year Stanfield Malin Surnas • Rockies
CA
2030 87.6% 91.0% 86.8% 72.4% 95.2% 117.7%
2035 84.8% 87.6% 87.1% 70.7% 92.7% 112.6%
2040 80.9% 82.2% 83.1% 72.9% 88.5% 103.4%
2045 79.1% 80.3% 81.6% 68.9% 86.2% 98.5%
20-Year $3.61 $3.72 $3.65 $3.01 $3.93 $4.79
The average of the 300 stochastic prices is similar to the expected price forecast
described earlier in this chapter. Figure 9.6 illustrates the simulated data for the stochastic
studies compared to the input data for the Henry Hub price hub. The stochastically derived
nominal levelized price for 20 years is $5.03 per dekatherm. These values likely would
converge to the expected price of $4.86 per dekatherm with a sample size much larger
than 300. The median price is closely aligned with the input price of$4.82 per dekatherm.
Another component of the stochastic nature of the forecast is the growth in variability. In
the first year, prices vary 7% around the mean, or the standard deviation as a percent of
the mean. This value is 39% by 2040 and 42% by 2045. Avista uses higher variation in
later years because the accuracy and knowledge of future natural gas prices becomes
less certain.
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Chapter 9: Market Analysis
Figure 9.6: Henry Hub Natural Gas Price Forecast
$16.00
■Average
$14.00 •25th Percentile
—50th Percentile
$12.00 ♦95th Percentile
E
•Deterministic Input
y $10.00
t
Q $8.00 ♦ ♦ —
♦ —
♦ ♦ —
Q $6.00 ♦ ♦
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$4.00
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N N N N M Cl) M M M Cl) Cl) Cl) CO M V It V lzr
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Figure 9.7 shows another visualization of Avista's natural gas price forecast assumptions.
This chart shows a histogram of the 20-year nominal levelized prices for Henry Hub to
demonstrate the skewness of the natural gas price forecast.
Figure 9.7: Henry Hub Nominal 20-Year Nominal Levelized Price Distribution
20%
18% 17%
V 16% 15% 15%
C
i 14%
3
v 12% 11%
0 10%
p 10%
>. 8%
8% 7%
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Chapter 9: Market Analysis
Regional Coal Prices
Coal-fired generation facilities are still an important part of the Western Interconnect. In
2023, coal met 14% of WECC loads — falling from 34% in 2001. Coal pricing typically
differs from natural gas pricing, providing diversification, and thus mitigating price volatility
risk. Natural gas is delivered by pipeline, whereas coal delivery is by rail, truck, or
conveyor. Coal contracts are typically longer term and supplier specific. Avista uses the
coal price forecast in Energy Exemplar's default database. Energy Exemplar's forecast is
based on FERC filings for each of the coal plants and that data is used to determine
historical pricing. Future prices are based on the EIA Annual Energy Outlook.
Coal price forecasts have uncertainty like natural gas prices, yet the effect on market
prices is less because coal-fired generation rarely sets marginal prices in the Western
Interconnect. While labor, steel, and transportation costs drive some portion of coal price
uncertainty, transportation is its primary driver. There is also uncertainty in fuel suppliers
as the coal industry is restructuring as less coal is mined. Given the relatively small effect
on Western Interconnect market prices, Avista chose not to model coal prices
stochastically.
Hydro
The Northwest U.S., British Columbia, and California have substantial hydro generation
capacity. Hydro resources accounted for 50% of generation in the Northwest in 2023, but
only 19% of generation in the Western Interconnect. A favorable characteristic of hydro
power with a reservoir is its ability to provide near-instantaneous generation up to and
potentially beyond its nameplate rating. Hydro generation is valuable for meeting peak
load, following general intra-day load trends, storing and shaping energy for sale during
higher-valued hours, and integrating variable generation resources. The key drawbacks
to hydro generation are its variability and limited fuel supply due to weather conditions.
The deterministic forecast uses a rolling 30-year median of hydro production including a
combination of historic water years and forecasted generation incorporating the
temperature change predictions in Representative Concentration Pathway (RCP) 4.5.90
Throughout the 20-year planning horizon, there is a greater percentage of forecasted
generation included in the 30-year period. For example, for planning year 2030, hydro is
based on a median of historic water years from 2000-2021 and forecasted hydro for years
2022-2029. See Figure 9.8 for a hydro comparison of this methodology with the former
average using an 80-year hydro record.
90 See Chapter 7 for more detail on the hydro forecast and climate assumptions included.
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Chapter 9: Market Analysis
Figure 9.8: Northwest Hydro Generation Comparison
20,000
-1929.2008 -1992-2021 -2023-2045
18,000
16,000
14,000
tv 12,000
C1
d
10,000
d
M 8,000
d
Q 6,000
4,000
2,000
OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUG SEP
Many forecasts use an average of the hydro record, whereas the stochastic study
randomly draws from the historical record. Avista's stochastic forecast incorporates the
same combination of the historic water years and forecasted hydro as used in the
deterministic study, however, hydro is randomly selected for the 300 iterations to simulate
risk of different hydro conditions. Figure 9.9 shows the average hydro energy is 13,230
aMW (median 13,426 aMW) in the Northwest over the 20-year study, defined here as
Washington, Oregon, Idaho, and western Montana. The chart also shows the range in
potential energy used in the stochastic study, with a 10th percentile water year of 11,320
aMW (-15%) and a 90th percentile water year of 14,735 aMW (+11
Figure 9.9: Northwest Expected Energy
20%
18%
16%
14%
12%
Z
Q 10%
O
d 8%
6%
4%
0
2% �% 2/o
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
o u> o o L o Ll o u> 0 LQ o � C uQ
O O O N N M M V V to In C2 (O h t�
Average Megawatts
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Chapter 9: Market Analysis
Wind Variation and Pricing
Wind is a growing generation source used to meet customer load. Western Interconnect
wind generation increased from nearly zero in 2001 to 11% in 2023.91 Capturing the
variation of hourly wind generation is an important fundamental for power supply models
due to the volatility of its generation profile, and the effect this volatility has on other
generation resources and electric market prices. Energy Exemplar recently populated a
larger database of historical wind data points throughout North America. This analysis
builds on previous work by incorporating a stochastic element to modify the wind pattern
annually. Avista uses the same methodology for developing its wind variation in previous
IRPs. The technique includes an auto correlation algorithm with a focus on hourly
generation changes. It also reflects the seasonal variation of wind generation.
To keep the analysis manageable, Avista developed 15 different hourly wind generation
profiles that are randomly drawn for each year of the 20-year forecast. By capturing
volatility this way, the model can estimate hours with oversupply compared with using
monthly average generation factors.
Solar
Solar is increasing its market share in the Western Interconnect. In 2023, solar was 9%92
of the total generation in the Western Interconnect, up from 2% in 2014 (both estimates
exclude behind the meter solar). The Aurora model includes multiple solar generation
shapes with multiple configurations, including fixed and single-axis technologies, along
with multiple locations within the 19 load areas. As solar grows, additional data will be
available and incorporated into future IRP modeling. A future new technique may include
multiple hourly solar shapes, like those used with wind, so the model can account for
solar variation from cloud cover.
Other Generation Operating Characteristics
Avista uses Energy Exemplar's database assumptions for all other generation types not
detailed here, except for Avista's owned and controlled resources. For Avista's resources,
more detailed confidential information is used to populate the model.
Forced outage and mechanical failure is a common problem for all generation resources.
Typically, the modeling for these events is through de-rating generation. This means the
available output is reduced to reflect the forced outages. Avista uses this method for solar,
wind, hydro, and small thermal plants; but uses a randomized outage technique for larger
thermal plants where the model randomly causes an outage for a plant based on its
historical outage rate, keeping the plant offline for its historical mean time to repair.
91 Wind represented 11.5% of Northwest generation in 2023.
92 Solar represented 2% of Northwest generation in 2023.
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Chapter 9: Market Analysis
Negative Pricing and Oversupply
Avista adjusted the Aurora model to account for oversupply in the Mid-Columbia market,
including negative price effects. Negative pricing occurs when available generation
exceeds demand. This generally occurs in the Northwest when much of the hydro system
is running at maximum capacity in the spring months due to high runoff and wind projects
are also generating without an economic incentive to shut off due to their pressure to
generate for the Production Tax Credit (PTC), environmental attributes (e.g., Renewable
Energy Credits (RECs)), or for contract obligations. While hydro resources are
dispatchable, they may not be able to curtail enough to prevent negative prices due to
total dissolved gas constraints forcing hydro to generate instead of spilling. This
phenomenon will likely increase as more wind and solar generation is added to the system
with tax credits in place or where environmental attributes are needed to meet clean
energy requirements. To model this oversupply effect in Aurora, Avista changes the
economic dispatch prices for several resources that have dispatch drivers beyond fuel
costs.
The first modeling change Avista made is to the hydro dispatch order by making hydro
resources a "must run" resource or last resource to curtail. To do this, hydro generation
is assigned a negative $30 per MWh price (2020$).93 The next change assigns an $8 per
MWh (2020$) reduction in cost for qualifying renewable resources to reflect a preference
for meeting state renewable portfolio standards (RPS); this price adjustment accounts for
the intrinsic value of the REC. The last adjustment is to include a PTC for resources with
this benefit. After these three adjustments, the model turns off resources in a fashion
similar to periods of excess generation seen today. In an oversupply condition such as
this, the last resource turned off sets the marginal price.
Greenhouse Gas Pricing
Many states and provinces have enacted greenhouse gas emissions reduction programs
with others considering such programs. Some states have emissions trading
mechanisms, others chose clean energy targets, and some chose both. Aurora can model
either policy, but different policy choices can result in varying impacts to electric wholesale
pricing. Clean energy target programs, such as Washington's Clean Energy
Transformation Act (CETA), generally depress prices due to the bias for increasing the
incentives to construct low marginal-priced resources. California's cap and trade program
has the opposite effect and pushes wholesale prices upwards. Avista includes known
pricing programs in Washington, California, British Columbia, and Alberta in its modeling
as a price adder. Oregon's Clean Energy Targets (HB 2021) are modeled as a maximum
emission constraint.
93 These plants cannot be designated with a "must run" designation due to the "must run" resources being
required to dispatch at minimum levels and for modeling purposes, hydro minimum generation is zero in
the event of low stream flows.
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Chapter 9: Market Analysis
Washington passed the Climate Commitment Act (CCA) in 2021 enacting the potential
for carbon pricing on Washington generation resources beginning in 2023.94 CCA rules
were released October 2022, and regulated entities continue to refine their understanding
of its complete impacts. The Washington State Department of Ecology (Ecology) is
responsible for implementing the CCA. Ecology is working on providing detailed
descriptions or examples to aid regulated entities such as Avista in how to accurately
calculate compliance costs. It is unclear how the CCA will ultimately impact energy
markets due to changes in linkage with California. Therefore, carbon pricing for
Washington continues to be extremely uncertain. Modeling methodologies will be updated
in a future resource plan once the full requirements are known. In the meantime, the
prices included in the analysis assume Washington and California will link their markets
and the CCA credit values are based on an independent consultant's price forecast.95
The price ranges used in the stochastic modeling are shown in Figure 9.10 and the
methodology96 is described below.
1) Utility controlled generation within Washington State — These plants assume all
GHG prices are included in the dispatch decision for all GHG emitting resources
beginning in 2031.
2) Non-utility owned generation within Washington State — These plants assume all
GHG prices are included in the dispatch decision for all GHG emitting resources
beginning in 2026.
3) Utility controlled generation within Washington State but serving other states —
This applies the pricing used from #2 above using the ratio of the utility's out of state
load share starting in 2026.
4) Northwest Imports — Any power imported into California or Washington incurs a
carbon price adder to transfer power and uses the pricing from #2 above based on the
default 0.437 metric ton per MWh GHG intensity rate.
94 Pricing relative to other emission sources was also enacted but is irrelevant to this IRP.
95 The carbon price forecast used in Avista 2025 Electric IRP is the same carbon pricing assumption used
in Avista's 2025 Natural Gas IRP.
96 Various approaches were discussed with the TAC at multiple meetings and through email. Input and/or
enhancements to this process were sought and were included based on the best available information at
the time of the analysis.
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Chapter 9: Market Analysis
Figure 9.10: Carbon Price AssuMPLIUllb
$350
......Floor — —Min Percentile:25%
••••••Input — —Mean — Median
$300 Percentile:95% — —Max ......Ceiling
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Q O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Regional Generation Source Forecast
This forecast assumes a continuing shift to clean energy resources across the Western
Interconnect over the next 20 years. Figure 9.11 shows the historical and forecast
generation for the U.S. portion of the Western Interconnect.97 In 2023, 58% of generation
came from clean energy, and is expected to increase to 73% by 2030 and 81% by 2045.
To achieve this clean-energy shift, while also serving new loads, solar and wind
production will displace coal and natural gas. Absent significant new long-term storage
technologies, some thermal resources will still be required to help meet system needs
during peak weather events, especially in Northwest winters, and they may also be
needed to recharge energy storage if wind or solar are not available after an event.
The Northwest will undergo significant changes in future generation resources. This
forecast expects coal, natural gas, and nuclear generation to be limited by 2045, and the
remaining requirements will be met with solar, wind, and hydro generation. As of 2023,
69% of the Northwest generation was clean, increasing to 88% in 2030 and 94% by 2045
as shown in Figure 9.12. Achieving these ambitious clean energy goals will require nearly
tripling wind generation and a nearly 12-fold increase in solar energy from the 2023
generation levels. This results in solar providing 11% and wind 24% of future generation.
97 Forecast is for the average of the 300 simulations.
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Chapter 9: Market Analysis
Figure 9.11: U.S. Western Interconnect Generation
120,000
■Other ■Hydro ■Nuclear ■Coal ■Wind ■Solar Natural Gas
100.000
_U)
} 80.000
60,000
M
L
40,000
Q
20,000
I
I
N M 41 W ti O Q) O N M L() (O M O O N M In W I- W O O N (M a lD rl- IM O O 11 7 V N
O O O O O O O O O N N N N N N N N N N M M M M M M O M M M V O V V V V
O O O O O O O O O O O O O O 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
Figure 9.12: Northwest Generation
35,000
■Other ■Hydro ■Nuclear ■Coal ■Wind ■Solar Natural Gas ■Petroleum
30,000
25,000
M
0 I
0) 20,000 — I
ME■■■■
15,000 '
N
N
Q
10,000
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N M I Uf <D r` N O O N M C LO <D r-- M M O N M V W W r� O M O
O O O O O O O O O N N N N N N N N N N M M M M M M M M M M V V a V V
O CD ID O CD O CD CD ID O CD O CD CD CD CD O CD CD CD al CD CD CD CD CD CD CD O O O O CD CD O O ID a, al O CD
N N N N N N. N N N N N . N N N N N N N N N N N N N N N N N N N N N N N N N N N N " N N N
Regional Greenhouse Gas Emissions
GHG emissions are likely to significantly decrease with the retirement of coal generation
and new solar/wind resources displacing additional natural gas-fired generation. Electric
generation related GHG emissions within the U.S. Western Interconnect were
Avista Corp 2025 Electric IRP 243

Chapter 9: Market Analysis
approximately 229 million metric tons in 2022, a reduction from the 1990 emissions level
of 234 million metric tons. Avista obtained historical data back to 1980 from the EPA; the
emissions minimum since 1980 was 161 million metric tons in 1983.
Avista's energy market modeling only tracks emissions at their source and does not
estimate assignment to each state from energy transfers, such as emissions generated
in Utah for serving customers in California. Figure 9.13 shows the percent totals for 2022
and the 2045 forecast. The largest emitters by state are Arizona and California, followed
by Wyoming, Colorado, and Utah. The four northwest states combined generate 14% of
the total emissions in the Western Interconnect.
By 2045, Avista estimates GHG emissions will fall to 18% of 1990 levels as shown in
Figure 9.14. All states will have a reduction in GHG emissions in this forecast. The
greatest reductions by percentage are New Mexico (98%), Utah (95%), Arizona (89%),
and Nevada (86%). The greatest reductions by metric tons are California (29 MMT),
Arizona (29 MMT), Utah (28 MMT), and New Mexico (26 MMT).
Figure 9.13: 2022 and 2045 Greenhouse Gas Emissions
50.0
45.0 ■2022 ■2045
c 40.0
0
N 35.0
WE 30.0
25.0
0
20.0 N
0
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aD
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Chapter 9: Market Analysis
Figure 9.14: Greenhouse Gas Emissions Forecast
350
�AZ MCA
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300 �MT �NV
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250 �WY —1990
HN ' I
200 I
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00 00 O CO CO (D O (D 0) 0) O O O O O N N N N N M M M M M
O O O O O O O O O O 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
N N N N N N N N N N N N N N N N N N N N N N N
Regional Greenhouse Gas Emissions Intensity
To understand the GHG emissions from the regional market Avista may purchase power
from, Avista uses regional emissions intensity per MWh to estimate the associated
emissions from these short-term acquisitions. Avista uses the mean values shown in
Figure 9.15 for each of the 300 simulations. Figure 9.15 below shows the mean, 25' and
75t" percentiles for regional GHG emissions intensity. The GHG emissions are included
from Washington, Oregon, Idaho, Montana, Utah, and Wyoming. Emissions intensity falls
as renewables are added and coal and natural gas plants retire or decrease dispatch, but
the intensity rate also depends on the year-to-year variation in hydro production. The
locations for Avista's area for potential market purchases is consistent with Washington's
Energy and Emissions Intensity report but is higher than Avista's likely counter parties for
market purchases. This figure also includes incremental regional GHG emissions to
evaluate efficiency programs. In this case, Avista determines the incremental regional
GHG emissions per MWh using a second forecast with additional load within the
Northwest system, then the change in emissions is compared to the change in load.
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Chapter 9: Market Analysis
Figure 9.15: Northwest Regional Greenhouse Gas Emissions Intensity
600
Mean •75th Percentile 025th Percentile
500
400
300
a ■
■
200 ■ ■
■
100 ■
F
0
to r` CO O O N M .e 61 to r` W to O N M a Un
N N N N M M M M M f") M M M M � 'T � 'T Iq
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Electric Market Price Forecast
Mid-Columbia Price Forecast
There are two wholesale prices forecasts within this resource plan, a deterministic version
where all 8,760 hours for the 20-year period are simulated and a stochastic version
simulating 300 of the 20-year hourly studies. Each study uses hourly time steps between
2026 and 2045. This process is time consuming when conducted 300 times for the
stochastic forecast. The 300 future simulations take more than one week of continuous
processing on 33 separate processor cores to complete. Time constraints limit the
number of market scenarios Avista is ultimately able to explore in each resource plan.
The increase in future storage resources within the marketplace requires optimization
techniques to determine pricing. This process significantly increases the modeling time
and requires the number of iterations to be reduced to 300. Analysis was performed to
ensure the 300 iterations was sufficient to encompass most of the distribution of
uncertainty.
The annual average of all hourly prices from both studies is shown in Figure 9.16. This
chart shows the annual distribution of the prices using the loth and 95th percentiles
compared to the mean, median and deterministic prices. The pricing distribution is
lognormal, as prices continue to be highly correlated with the lognormally distributed
natural gas prices. The 20-year nominal levelized price of the stochastic study is $44.14
per MWh (with CCA) and $42.77 per MWh (without CCA) and is shown in Tables 9.7, 9.8
and 9.9. Tables 9.8 and 9.9 include the super peak evening (4 to 10 p.m.) period to
illustrate how prices behave during this high-demand period where solar output is falling,
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Chapter 9: Market Analysis
and rising prices encourage the dispatch of other resources. Pricing with CCA represents
the power price for the Washington zone, whereas the price without CCA is an average
of the Avista and Mid-Columbia areas.
figure 9.16: Mid-Columbia Electric Price Forecast Range
$80
■Average •10thpercentile —Median A 95th percentile *Deterministic
$70 A
$60 ♦
$50
� $40
a
e» $30
$20
$10
$0
i0 r- co Q1 O N M a N O N. O M O N M h
N N N N M 0 `O M M M 0 `O `O C> a 7 7 7 0
O O O 0 O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Table 9.7: Nominal Levelized Flat Mid-Columbia Electric Price Forecast
Levelized with - .
CCA without CCA
6==M� ($IMWh) ($/MWh)�
Deterministic $45.45 $44.37
Stochastic Mean $44.11 $42.77
10th Percentile $36.86 $38.42
50th Percentile $41.17 $42.85
95th Percentile $47.06 $48.05
Average on-peak prices between 7 a.m. and 10 p.m. on weekdays plus Saturdays have
historically been higher than the remaining off-peak prices. However, this forecast shows
off-peak prices outpacing on-peak prices on an annual basis beginning in 2029 due to
increasing quantities of solar generation expected to be placed on the system, thus
depressing on-peak prices. As more solar is added to the system, this effect spreads into
the shoulder months. Only in the winter season, where solar production is lowest, does
the traditional relationship of today's on- and off-peak pricing continue.
Depending on the future level of energy storage and its duration, market price shapes
could flatten out rather than inverting the daytime price spread. Mid-day pricing will be
low in all months going forward, driving on-peak prices lower. Super peak evening prices
after 4 p.m., when other resources will need to dispatch to serve load, can be high if
startup costs affect market pricing as expected in this forecast.
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Table 9.8: Annual Average Mid-Columbia with CCA Electric Priuvb ($/MWh)
Year Fla, Off- - Super
LPeak
Peak
2026 $41.98 $40.46 $43.12 $54.18
2027 $38.14 $38.58 $37.82 $50.78
2028 $35.40 $37.03 $34.18 $46.43
2029 $35.04 $36.64 $33.84 $45.19
2030 $39.18 $40.90 $37.89 $48.68
2031 $44.10 $46.40 $42.38 $53.18
2032 $44.33 $47.09 $42.27 $53.32
2033 $45.40 $48.29 $43.23 $54.77
2034 $45.55 $48.72 $43.17 $54.82
2035 $46.71 $49.96 $44.27 $56.59
2036 $46.40 $49.74 $43.90 $56.44
2037 $47.66 $51.45 $44.82 $57.60
2038 $47.77 $51.51 $44.98 $57.83
2039 $48.48 $52.35 $45.58 $58.86
2040 $49.59 $53.79 $46.43 $59.08
2041 $50.01 $54.44 $46.68 $59.91
2042 $52.31 $56.90 $48.88 $62.96
2043 $52.97 $57.66 $49.45 $64.16
2044 $53.84 $58.61 $50.27 $65.39
2045 $55.07 $59.83 1 $51.48 1 $67.76
20-Year 1 $42.15 $44.51 1 $40.38 1 $52.11
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Table 9.9: Annual Average Mid-Columbia without CCA Electric Pr iut:s ($/MWh)
2026 $41.61 $40.42 $42.50 $53.43
2027 $37.88 $38.70 $37.26 $50.15
2028 $35.13 $37.19 $33.57 $45.89
2029 $34.57 $36.64 $33.01 $44.51
2030 $38.56 $40.85 $36.84 $47.91
2031 $43.00 $45.74 $40.96 $52.00
2032 $42.74 $45.92 $40.36 $51.69
2033 $43.82 $47.20 $41.29 $53.10
2034 $43.92 $47.54 $41.19 $53.13
2035 $44.93 $48.59 $42.18 $54.75
2036 $44.50 $48.21 $41.72 $54.48
2037 $45.69 $49.82 $42.61 $55.59
2038 $45.66 $49.68 $42.64 $55.67
2039 $46.29 $50.42 $43.19 $56.64
2040 $47.28 $51.69 $43.96 $56.76
2041 $47.66 $52.29 $44.19 $57.58
2042 $49.92 $54.68 $46.35 $60.58
2043 $50.52 $55.38 $46.88 $61.73
2044 $51.24 $56.12 $47.58 $62.81
2045 $52.39 $57.26 $48.71 $65.12
20-Year $40.87 $43.58 $38.83 $50.70
Figures 9.17 through 9.20 show the average prices for each hour of the four seasons for
every five years of the price forecast. The spring and summer prices generally stay flat
throughout the 20 years as these periods have larger quantities of hydro and solar
generation to stabilize prices, but mid-day prices decrease over time while prices for the
other time periods increase. Unless long-term energy storage materializes, winter and
autumn prices will have larger price increases due to less available solar energy. With
this analysis, current on/off-peak pricing will need to change into different products such
as a morning peak, afternoon peak, mid-day, and night. Pricing for holidays and
weekends likely will be less impactful on pricing except for the morning and evening
peaks. Future pricing for all resources will need to reflect these pricing curves so they can
be properly valued against other resources.
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Figure 9.17: Winter Average Hourly Electric Prices (December — February)
$250
2030 2035
2040 2045
$200
s $150 —
a $100
69.
$50 -
$0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Figure 9.18: Spring Average Hourly Electric Prices (March — June)
$250
2030 2035
—2040 2045
$200
$150
a $100
$50
j
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
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Figure 9.19: Summer Average Hourly Electric Prices (July - September)
$250
- 2030 2035
2040 2045
$200
$150
L
a $100
$50
$0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Figure 9.20: Autumn Average Hourly Electric Prices (October— November)
$250
- 2030 - 2035
2040 2045
$200
$150
L
$100
69
$50
$0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
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Scenario Analyses
Electric wholesale market prices will have an impact on this resource plan depending on
how each resource option performs compared to other resources. This comparison uses
market prices along with how each resource performs when customers need them (e.g.,
winter sustained peak). Market price forecasts can be rather computer processor and
time intensive. However, understanding specific effects on the marketplace are important
to understand the risks involved with resource choice. Avista studied three additional
scenarios beyond the 300 simulations of the Expected Case. Avista modeled each
scenario deterministically. Deterministic studies are sufficient because the objective of
the scenarios is to understand the effect of the underlying change in assumption of the
plan. The portfolio sensitivities and market scenarios conducted forthis IRP are discussed
below.
Natural Gas Pricing Scenario
Low natural gas prices will impact resource selection by lowering electric prices. This
scenario assumes 25t" percentile natural gas prices from the Expected Case stochastic
study. The high pricing scenario uses the 90t" percentile of the same Expected Case data
set. Both scenarios rely on the Expected Case capacity expansion study. Figure 9.21
compares the 20-year levelized cost of these scenarios to the Expected Case at the Henry
Hub natural gas price. The high gas price scenario is 144% above, while the low-price
scenario is 26% below the Expected Case. These gas price scenarios are useful in
determining the viability of future resource options given possible changes in natural gas
prices. For example, low natural gas prices will make renewable projects less economic
while high natural gas prices will make them relatively more economic.
Figure 9.21: Change in Henry Hub Natural Gas Prices
$8.00
$7.28
$7.00
$6.00
$5.06
$5.00
$4.00 $3.90
$3.00
$2.00
$1.00
$0.00
Low Price Scenario High Price Scenario Expected Case
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Scenario Electric Price Results
The results of these scenarios show a variety of market price impacts from changes in
key assumptions. Figure 9.22 presents the nominal levelized prices for each scenario on
a 20-year basis compared with the Expected Case's deterministic study assuming
Washington delivery. The No CCA scenario assumes no CCA in Washington. The
deterministic study is shown to eliminate other factors for the comparative analysis. For
example, the only change in the study assumptions is the specific input rather than
stochastic assumptions. The annual prices used to estimate the levelized costs for each
scenario are shown in Figure 9.23.
Figure 9.22: Mid-Columbia Nominal Levelized Prices Scenario Analysis
$60.00
$55.18
$50.00 $47.01
$42.58 $41.98
$40.00
$30.00
$20.00
$10.00
$0.00
L Expected Case
The natural gas pricing scenarios show how a 144% increase in natural gas prices causes
a 17% increase in electric market prices. When natural gas prices are 26% lower than the
Expected Case, the resulting electric market prices are 9% lower.
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Figure 9.23: Mid-Columbia Annual Electric Price Scenario Analysis
$70.00
$60.00
$50.00
L
$40.00
N
Q
e» $30.00
$20.00 —Deterministic($47.01)
—Low NG Prices($42.58)
$10.00 —High NG Prices($55.18)
—No CCA($41.98)
$0.00
W I._ 00 0) O N M V Lf) t0 I'- 00 T O N M N
N N N N M M M M M M M M M M � I.* V V
O O O O O O O O C. O O O O O O C. O O O O
N N N N N N N N N N N N N N N N N N N N
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Chapter 10: Portfolio Scenario Analysis
10. Portfolio Scenario Analysis
The 2025 Preferred Resource Strategy (PRS) is Avista's approach to meet future load
growth and replace aging generation resources through 2045. The future's actual results
are often different from the IRP's Expected Case forecast used to develop the PRS,
because of this, the future resource strategy will change as time progresses to respond
to new information about markets, resources, and regulations. This IRP identifies
alternative optimized resource strategies for different underlying assumptions to
understand how Avista may respond to new information. Resource decisions may change
depending on how customers use electricity, the availability of existing resources, how
the economy changes, and how greenhouse gas (GHG) emission policies evolve. This
chapter investigates the cost and risk impacts to the PRS under different future scenarios
the utility may face, as well as alternative resource portfolios.
Section Highlights
• Energy storage and demand response are the most viable options to meet
new short-term capacity needs.
• Nuclear energy will be needed to meet extreme load growth scenarios.
• Early acquisition of wind generation is driven by the federal government's
Inflation Reduction Act (IRA) and high wholesale electric market prices.
• The amount of wind energy selected in the PRS is sensitive to power
market prices, the price of wind, and the availability of low-cost
interconnects. A change in these parameters could shift resource choices.
• Natural gas resources remain the lowest cost capacity resource for Idaho
customers so long as transmission and fuel storage are constructable.
Portfolio scenarios are representative of studies requested by the Technical Advisory
Committee JAC) or regulatory requirements. Most of the scenario studies address
uncertainty such as: the Northeast Combustion Turbine's (CT) retirement date, a data
center locating in the service area, warmer future weather conditions, significant
economic condition changes, building electrification, transportation electrification,
availability of local wind resources, loss of IRA tax benefits, future required planning
reserve margins (PRM), and viability of new resource technologies. In addition to
alternative portfolio choices, Avista tested a portfolio impact in which the Climate
Commitment Act (CCA) is repealed and how the PRS is sensitive to much higher or lower
natural gas prices. All portfolios are assigned a portfolio number based upon the order
added to the list of studies. The full list of scenarios and assigned numbers are shown in
Table 10.1 by load, resource availability, and other categories.
Avista plans to issue a Request for Proposal (RFP) for new resources in 2025 with an on-
line date by the end of the decade. This RFP will help inform short-term risks such as
resource availability, provide options to replace the Northeast CT, and additional time to
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measure load growth changes. Further, the RFP can be informative about serving a data
center (if one requests service), and how it could elevate short-term load risks. Most of
the significant risks identified in this analysis stem from higher load levels. The
electrification of transportation and buildings poses the greatest long-term risk. Given the
limited supply of infrastructure, manufacturing capacity and required workers,
electrification changes will likely occur at a more gradual pace, giving utilities time to
respond to trends and soften the shock to the power supply system. However, the high
load scenarios are large enough to justify earlier planning for long lead items such as
transmission and distribution system upgrades. A new large industrial load may require
additional generation at a faster pace forcing larger system upgrades.
Another risk identified in the scenario analysis would occur if Avista needed to change
course from the PRS due to a clean energy requirement in Idaho. The inability to site a
new natural gas resource or higher natural gas construction costs could change Avista's
resource choices. While natural gas-fired generation remains a cost-effective option for
Idaho customers in this plan; technology, turbine pricing, or public policy changes could
require a reduction of those resources to serve Idaho customers. Based on the current
political environment, this would most likely come from a federal policy change or a
significant cost reduction in non-gas generation and storage from new technologies.
Table 10.1: Scenario List
Load Scenarios 1"MW Resource Availability M
•
#5 - Low Growth #4 - Clean Resource Portfolio #2 -Alternative Lowest
by 2045 Reasonable Cost
#6 - High Growth #11 - 500 MW Nuclear in 2040 #3 - Baseline Least Cost
Portfolio
#7 - 80% Washington Building #14 - Power to Gas #10 - Maximum Washington
Electrification by 2045 Unavailable Customer Benefit
#8 - 80% Washington Building #21 - Regional Transmission
Electrification by 2045 & High not Available
Transportation Electrification
#9 - 80% System Building #22 - 2026 Northeast CTs #13 - 30% PRM
Electrification by 2045 & High Retirement
Transportation Electrification,
No New NG CTs
#18 - 200 MW Data Center in #23 - On-System Wind Limited #15 - Minimal Viable CETA
2030 to 200 MW Target
#19 - RCP 8.5 Weather #24 - No IRA Tax Incentives #16 - Maximum Viable CETA
Target
#20 - 80% System Building #25 - 2035 Northeast CTs #17 - PRS Constrained to the
Electrification by 2045 & High Retirement 2% Cost Cap
Transportation Electrification
Scenario No New NG CTs with
RCP 8.5 Weather
#26- PRS w/CCA repealed
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Load Scenarios
Avista conducted eight future load growth scenarios to understand the impact on the
resource portfolio. These load scenarios include changes in customer growth from
population, understanding the impact of building electrification, quantifying high rates of
transportation electrification, evaluating a new large system load (such as a data center),
and lastly determining the impact of different future weather conditions on planning.
Chapter 3 includes documentation regarding the impact of the load forecast.
Low and High Load Growth
The low economic growth scenario results in an annual average growth rate of 0.34%
compared to the Expected Case's growth rate of 0.91% per year. The high economic
growth scenario increases load at 1.75% per year. The change in load either increases
or decreases the amount of generation selected in the PRS, but generally uses the same
resource types to solve resource requirements, except for removing nuclear energy in the
low growth scenario for Washington. Table 10.2 outlines the low and high growth resource
selections compared to the PRS over the 20-year study period, the present value of
revenue requirement (PVRR), and the 2030 and 2040 average energy rates.
fable 10.2: Low and High Load Growth Scenarios
Washington.
LoadsPrefer ed Economic Economic Preferred conomic Economic
Resource G rowth Growth Resource Growth Growth
MLji Strategy Loads..i Loads Strategyt Loads
Natural Gas 0 0 131 275 277 431
Solar 311 149 310 0 0 0
Wind 1,307 1,268 1,302 119 66 158
Energy Storage 261 104 370 0 0 0
i� Power to Gas 394 394 394 0 0 0
(z Nuclear 100 0 349 0 0 0
Geothermal 20 20 20 0 0 0
Biomass 64 64 7 3 3 3
Demand Response 70 61 120 17 71 11
EE-Winter Capacity 1 156 156 156 49 49 49
EE-Summer Capacity 1 1111 1111 1111 38 38 38
PVRR (Millions) $10,924 $10,641 $11,494 $4,758 $4,711 $4,964
2030 Rate ($/kWh) $0.130 $0.131 $0.128 $0.112 $0.112 $0.109
2045 Rate($/kWh) $0.248 $0.242 $0.262 $0.180 $0.189 $0.167
By 2030, the rate impact between the scenarios is negligible, but generally higher loads
reduce energy rates as the existing system's fixed costs are spread out over more load.
The rate impact for Idaho customers follows, where higher loads reduce the energy rates
(-7.3% in 2045) even though power costs are slightly higher. In the low load scenario, the
opposite occurs for Washington customers, where resource options are limited or cost
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constrained to account for the social cost of greenhouse gas (SCGHG), and lower loads
reduce the PVRR by avoiding higher priced resources. The high load scenario rates
increase as more nuclear and energy storage is required.
...:presentative Concentration Pathways (RCP) 8.5 for Winter Planning
Avista uses both forecasted and historical temperatures to normalize future weather for
estimating future customer loads. For the summer, Avista uses a temperature forecast
with the RCP 8.5 climate future as described in Chapter 5, but in the winter months Avista
uses RCP 4.5. The difference between these two temperature futures is the RCP 8.5
scenario has warmer temperatures. For the energy load forecast, a rolling 20 years of
historical and forecasted temperatures are used for each month. But for peak planning,
only the summer months use a 20-year rolling average and the winter uses a 76-year
rolling average. Avista uses a wider range for winter due to the wider distribution in cold
temperatures compared to the summer's narrower distribution of hottest temperatures.
Avista is relying on the RCP 8.5 temperatures for the summer season, as recent history
(2020 to 2024) shows summer months are trending warmer than the RCP 8.5 forecast.
But actual winter temperatures are colder than the RCP 8.5 climate forecasts. Due to the
risk of cold winters and its impact on customers if Avista does not have adequate
generation, Avista does not believe using a warmer temperature forecast for resource
planning is prudent due to the significant risk of not being able to serve customers in the
event of cold weather similar to the last two winters. Regardless of Avista's preference,
this scenario shows the impact on the resource strategy of using RCP 8.5 year-round.
The result of the study is in Table 10.3. In Washington, there is a shift to use less winter
capable resources such as the reduction in power to gas and biomass generation, but
this is offset with increases in solar, wind, energy storage, and nuclear. The lower winter
loads reduce the need for both natural gas and wind for Idaho. Using the RCP 8.5
temperatures does lower costs due to the shift in generation and less energy sales, but
due to lower energy sales, the cost per kWh is higher.
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fable 10.3: RCP 8.5 Temperatures for Winter Planning
hmm[ Washington
Preferred 8.5 Preferred 8.5
esource Weather Resource We th
Strategy Strategyl :2
Natural Gas 01 0 275 229
Solar 311 317 0 0
Wind 1,307 1,322 119 111
Cn Energy Storage 261 325 0 0
Power to Gas 394 364 0 30
m Nuclear 100 108 01 0
Geothermal 20 20 0 0
Biomass 64 7 3 3
Demand Response 70 70 17 17
EE-Winter Capacity 156 156 49 49
fESu E- mmer Capacity 111 111 381 38
PVRR (Millions) $10,924 $10,907 $4,758 $4,752
2030 Rate ($/kWh) $0.130 $0.132 $0.112 $0.113
2045 Rate ($/kWh) $0.248 $0.248 $0.180 $0.182
Electrification Studies
Several electrification studies were requested by the TAC to better understand the impact
on the electric resource needs and cost of the system of extreme load changes. Building
electrification studies were designed to estimate impacts to the total cost to serve
customers considering fuel savings to the LDC98 natural gas system. The four
electrification scenarios include:99
• Washington Building Electrification (#7): Isolating building
electrification for just the Washington portion of the system where
natural gas LDC demand is 80% lower in 2045 than forecasted in
2026. Electric loads are 356 MW higher for winter peaks with an
average load increase of 107 aMW.
• Washington Building Electrification & High Transportation
Electrification (#8): uses the same building electrification assumptions
as scenario #7 but adds an equivalent of 246,000 electric vehicles to
the system by 2045 for a total of 806,000 EV equivalents. This adds
127 MW of winter peak load compared to#7 and 76 aMW of additional
energy obligations by 2045.
98 Local Distribution Company
99 A summary of load forecasts is included in Chapter 3.
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• Building Electrification & High Transportation Electrification w/o NG
(#9): This scenario adds to #8 by also electrifying buildings for the
Idaho LDC. In this case, Idaho's natural gas demand in 2045 is 80%
less than its 2045 forecasted natural gas load. This adds 300,000 EV
equivalents to the Idaho electric loads. In total, 1 million EV
equivalents are included in this scenario. To electrify Idaho's buildings
and transportation adds 520 MW to the 2045 winter peak and 219
aMW of energy.
• Building Electrification & High Transportation Electrification w/o NG
with RCP 8.5 (#20): This scenario adjusts the load in scenario #9 to
have warmer temperatures in the winter used in scenario#9 discussed
above.
In the scenarios where the Idaho service area has heavy adoption of building and
transportation electrification, the resource selection does not consider new natural gas as
a resource option. While building natural gas generation to serve electric load is an option
in Idaho, it is counter to the point of removing direct customer natural gas as the efficiency
of creating energy in the natural gas turbine is less then burning directly for space heat.
However, the study does retain Coyote Springs 2 for serving Idaho customers. Even
though natural gas is not an option used in this study, preliminary analysis indicates it
would be a lower cost option to serve the increased load than the portfolio results shown
below.
The increasing electrification loads result in both higher costs and rates due to the lack of
low-cost resources to serve new capacity and energy needs in addition to the added cost
to improve the transmission and distribution system. To serve these higher loads, the
capacity expansion model selects solar, nuclear, energy storage, and energy efficiency
to meet this demand.
Looking at the impact on the electric system in isolation, shows the total cost impact to
customers but does not show the impact to the natural gas system from the lost load.
Avista created a simplified natural gas planning model within its electric capacity
expansion model to consider the impacts to the natural gas LDC system. These impacts
include increased load to non-Avista electric utilities serving Avista's natural gas
customers100 and the cost to building owners for converting an existing natural gas forced
air and water heating system to electric. The most appropriate way to illustrate the cost
and benefits of building electrification is to compare scenario #7 to the PRS, as it isolates
the building electrification rather than including the transportation load. The levelized
incremental total customer costs are 25% higher when using electric to space and water
heat between 2043 and 2045 (this period is selected as it shows a high saturation of load
100 Approximately 25% of Washington natural gas customers have a non-Avista electric provider.
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Chapter 10: Portfolio Scenario Analysis
switching) as shown in Figure 10.1 . This increase includes estimated costs on other
electric utilities and the customers' site conversion costs.
aN � 10.4: Electrificat,%,, Scenarios
Washington0.
Preferred PRIM! PRM
Resource
&ROL
Strate
Natural Gas Strategy 0 0
Solar 311 210 311
Wind 1,307 1,308 1,315
U) Energy Storage 261 131 419
io Power to Gas 394 394 394
Nuclear 100 108 100
Geothermal 20 20 20
Biomass 64 64 64
Demand Response 70 73 73
EE-Winter Capacity 156 156 156
EE- Summer Capacity 111 111 111
PVRR (Millions) $10,924 $10,880 $11,083
2030 Rate ($/kWh) $0.130 $0.130 $0.132
2045 Rate ($/kWh) $0.248 $0.244 $0.252
Natural Gas 275 213 300
Solar 0 105 0
Wind 119 123 125
M Energy Storage 0 0 25
is Power to Gas 0 0 0
m Nuclear 0 0 0
Geothermal 0 0 0
Biomass 31 3 3
Demand Response 171 17 17
EE-Winter Capacity 491 49 49
EE- Summer Capacity 381 38 38
PVRR (Millions) $4,758 $4,734 $4,781
2030 Rate ($/kWh) $0.112 $0.112 $0.112
2045 Rate ($/kWh) $0.180 $0.180 $0.183
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The intent of the analysis is not only to identify what the system and customer costs of
transiting customers to electric heating, but to understand how it lowers GHG emissions.
In this case, between 2043 and 2045, the total emissions are 1.3 million metric tons lower
or 22%, but the cost per ton is $1,144 per ton of savings. Overall, the study found the
Ievelized cost per ton of savings is $828 per ton. As the cost of reducing emissions
exceeds the social cost of greenhouse gases (SCGHG), the economic benefits of rapidly
electrifying buildings are not justified.
Figure 10.1: 2043-2045 Washington Electrification Cost
$3,500
C
$3,000
$2,500
u7
Nt
C) $2,000
N
M
0
$1,500
N
$1,000
0
CU $500
Q $0 Li- rred Resource Strategy 7-WA Building Electrification
■Other Utility Cost Impacts $0 $37
■NG Site Conversion Cost $0 $118
■Natural Gas Idaho $172 $175
■Natural Gas Washington $369 $332
[EWElectric Idaho $626 $639
■Electric Washington $1,636 $2,012
Total $2,803 $3,313
Large Load/Data Center Scenario
Due to increasing artificial intelligence computing demand and growth in the technology
space, large data centers are searching for electric service at any utility with the ability to
accommodate their energy needs. Most data centers desire interconnection within 36
months but are finding few utilities able to accommodate the demand without building
new generation resources. Data center size ranges between 100 MW and 500 MW of
constant demand. Large new loads on the electric system have multiple impacts, such as
meeting energy requirements, resource adequacy, interconnection, and rate design to
isolate existing and future traditional customers from the incremental costs the large load
brings to the system. This scenario illustrates the impact of a 200 MW load in the
Washington service territory. The study assumes the existing cost allocation methodology
where costs are shared based on load share includes this higher load, effectively moving
existing generation from Idaho to Washington customers. Furthermore, the new load
share must be met with renewable energy following CETA requirements, but with the
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change in the cost sharing ratio, Idaho customers would need additional capacity to offset
previously allocated generation.
The results of the analysis,shown in Table 10.5, indicate Idaho must add an additional 95
MW of natural gas CTs and energy efficiency to offset the existing lost capacity (from the
updated PT ratio allocation with an additional 200 MW of load in Washington) and replace
the wind now needed to serve Washington's new load. For Washington, additional solar,
energy storage, nuclear, and energy efficiency meets the resource need. Rates in
Washington are lower as this load increase has a high load factor to absorb the higher
system cost. Idaho has slightly higher rates due to losing a small amount of wind and
increasing its energy efficiency programs.
Table 10.5: Large Load Impacts
Washington
bResource Preferred Center in Preferred Center in Resource 2030
StrategMI Strategy 0
Natural Gas 0 0 275 370
Solar 311 632 0 0
Wind 1,307 1,440 119 0
Energy Storage 261 329 0 0
is Power to Gas 394 394 0 0
m Nuclear 100 197 0 0
Geothermal 20 20 0 0
Biomass 64 64 3 3
Demand Response 70 73 17 17
EE-Winter Capacity 1 1561 1631 49 58
EE- Summer Capacity 1111 1161 38 44
PVRR (Millions) $10,924 $11,794 $4,758 $4,871
2030 Rate ($/kWh) $0.130 $0.131 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.237 $0.180 $0.187
The impact of the large load on the non-participating customers illustrates how a large
new load will require a creative rate design structure to serve the demand. This scenario
assumes a relatively small 200 MW data center, if the data center is closer to 500 MW
without curtailment abilities, the impact to customers begins to add additional long-term
complexity where the data center demand utilizes the lower cost resource alternatives
and forces future load growth to be served with higher cost future technologies. It may
also require significant transmission additions to bring generation to load centers.
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Resource Availability Scenarios
The IRP resource options are uncertain in terms of the quantity available, and in some
cases, the cost to bring those resources to the system. These scenarios quantify how
specific resource assumption changes could impact resource selection or the cost of the
portfolio. The resource availability scenarios include changes to the following
assumptions:
• Northeast CT retirement date (#22 and #25)
• Limitation of wind availability without new transmission (#23)
• Not building regional transmission to SPP/MISO (#21)
• Excluding power to gas as a resource (#14)
• Elimination of the IRA incentives (#24)
• Adding nuclear energy early (#11)
• No longer utilizing natural gas generation (#4)
Northeast Retirement
Northeast is a two-unit combustion turbine built in 1978 and located in northeast Spokane.
The facility's total capacity is 66 MW in the winter and 42 MW in the summer. The plant
is fully depreciated and provides the system with non-spinning reserves as it is limited to
50 hours of annual operation by its air permit. In the summer of 2024, the plant passed
its local emission's testing and is permitted to operate through 2029 and may be extend
to 2032 if it passes its emission test in 2029. This IRP's PRS assumes the plant is
available to the system through 2029. The Northeast site is a potential location for new
future resources to re-use the interconnection. The site does have the benefit of being
within a load center, lowering system energy losses. Avista studied two scenarios to
illustrate the impacts of either retiring the resource early in 2025 or retaining the facility
through 2034 as shown in Table 10.6.
Retiring the plant early changes the resource portfolio immediately, by requiring energy
storage and an increase to demand response in 2026 along with moving wind generation
to 2028. Due to the early replacement capacity, there is not enough time to develop a
new natural gas resource to meet Idaho's load deficit. This early shutdown raises 2030
rates by 0.7% in Washington and 0.9% in Idaho compared to the PRS. Although in the
long term, Washington's rates are 0.8% higher in 2045 and Idaho's are only 0.4% higher.
If Avista continues to operate the plant through 2034, the portfolio also selects resources
in an analogous way to closing early, but the need for energy storage is reduced to 36
MW for Idaho and the natural gas CT is deferred to 2037, although additional demand
response is needed by 2029. From an average cost of energy perspective, delaying
retirement has no material rate impact for either state in 2030, but in 2045, Idaho sees
rates 0.7% higher and Washington has no impact.
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The results indicate shutting down early and later both have similar long term rate impacts
on customers, but from a PVRR point of view, there is only 0.02% reduction in cost to
shutting down the plant in 2034 versus 2029. Given the minimal cost differences from
these scenarios, a 2029 shut down is a reasonable retirement date. Having a firm
retirement date for this facility allows the utility to plan for its exit and elevates risks to
maintain the aging facility when a failed emission test or breakdown could require the
utility to quickly respond to its forced retirement. Avista will be seeking energy and
capacity options in 2025 as part of its all-source RFP and will determine if replacing the
lost capacity with energy storage, natural gas, or an unknown option is the best way to
serve all customers.
T_1-1_ AA L1,rtheast CT Analysis
. .
Preferred Northeast Northeast Preferre Northeast Northeast
Resource Retires Retires Resourc Retires Retires
Strategy Early.1 Late Strategil'i Earlyl Late
Natural Gas 0 0 0 275 243 254
Solar 311 311 312 0 0 0
Wind 1,307 1,221 1,306 119 180 122
4 Energy Storage 261 274 261 0 57 36
i6 Power to Gas 394 394 394 0 0 0
Nuclear 100 122 100 0 0 0
Geothermal 20 20 20 0 0 0
Biomass 64 64 64 3 3 3
Demand Response 70 73 70 17 17 19
EE-Winter Capacity 1 156 156 156 49 49 49
EE- Summer Capacity 1111 1111 1111 381 381 38
PVRR (Millions) $10,924 $10,993 $10,922 $4,758 $4,775 $4,758
2030 Rate ($/kWh) $0.130 $0.131 $0.130 $0.112 $0.113 $0.112
2045 Rate ($/kWh) $0.248 $0.250 $0.248 $0.180 $0.181 $0.182
Wind Limitations
Avista assumes 500 MW of wind is available on its system without major transmission
expansion. It is possible other utilities or even data centers could consume a portion of
the 500 MW and take the energy off Avista's system. The intent of this scenario is to
understand resource selection changes if there is less low-cost interconnection wind
available than assumed by the PRS. Future RFPs will determine if this risk materializes,
but the impact to the portfolio results have minimal rate impacts in the short term. Energy
rates increase by 2045 as higher cost resources will be required to replace wind, resulting
in 3.3% higher rates for Washington and 0.5% higher for Idaho.
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From a system perspective, the results of the study show (as shown in Table 10.7) a small
increase from solar and natural gas due to losing 339 MW of wind, but a 54 MW increase
in nuclear generation. Due to the nuclear additions, 53 MW less of energy storage is
needed.
Table 10.7: On-System Wind Limitations
Washington
• On-
Preferred
Resource wind Resource wind
I a Strategy limited to StrategML_Iimited to
Natural Gas 0 0 275 287
Solar 311 325 0 0
Wind 1,307 994 119 93
�, Energy Storage 261 208 0 0
o Power to Gas 394 394 0 0
Nuclear 100 154 0 0
Geothermal 20 20 0 0
Biomass 64 64 3 3
Demand Response 70 73 17 17
EE-Winter Capacity 156 156 49 49
EE- Summer Capacity 1111 1111 381 38
PVRR (Millions) $10,924 $11,030 $4,758 $4,781
2030 Rate ($/kWh) $0.130 $0.131 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.256 $0.180 $0.181
Regional Transmission
Avista included a 300 MW new transmission line to the eastern interconnect in the PRS
and in the remaining scenario analyses. Avista assumes this line would allow Avista to
import up to 300 MW (prior to energy losses) of energy when wind in eastern Montana is
not available, and it may allow Avista to sell excess generation to other interconnects
when prices are higher in the eastern interconnect. There are two main value streams for
this project. The first is capacity value during reliability events. Avista studied this value
early in the PRS development and found this benefit alone justified participation. The
second major value is the ability to arbitrage the eastern markets with Mid-C power. Avista
has not shared this value in the IRP as it will be prepared in the final decision making of
this project. The intent of this scenario is not to look at the cost differences between this
scenario and the PRS, but to focus on the resource changes if the project is cancelled or
even delayed.
The results of this study indicate an increase in energy storage will be the main
replacement capacity. While there are minor changes in other generation types, the
model pushes the need forward in time for these resources. This includes acquiring wind,
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solar, and storage in 2032 for Washington instead of the transmission line, and for Idaho
acquiring a larger natural gas turbine in 2030.
Table 10.8: No Regional ) ansmission
Washington
Regional
availablePreferred Transmission Preferred Transmission
Resource not available Resource not
StrategyStrategy
Natural Gas 01 0 2751 287
Solar 311 320 0 0
Wind 1,307 1,274 119 93
Energy Storage 261 419 0 0
Power to Gas 394 394 0 0
m Nuclear 100 110 0 0
Geothermal 20 20 0 0
Biomass 64 64 3 3
Demand Response 70 55 171 17
EE- Winter Capacity 156 156 491 49
EE- Summer Capacity 111 111 381 38
No Power to Gas Project:
The PRS includes both hydrogen and ammonia fueled projects for power to gas (P2G)
resources. P2G options include co-firing hydrogen with natural gas at Coyote Springs 2
and building new ammonia fueled CTs. Both options are viable alternatives to provide
dispatchable clean energy. This scenario is designed to understand the portfolio and cost
changes without these resources as some parties advocate not to burn these fuels due
to NOx emissions. These fuels will require a new fuel supply chain and may include a
hydrogen pipeline system and on-site storage of ammonia. Both supply chains are
available in other parts of the country and world, not just in the northwest.
Without P2G as a fuel, the portfolio will require more energy storage (288 MW) and
nuclear energy (122 MW), and less wind by 93 MW. Moving from P2G fuels to shorter
term energy storage and nuclear increases energy rates in Washington by 11.1% in 2045
and 4.1% in Idaho. Idaho sees higher rates because the scarce wind resources are
reallocated to Washington.
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Table 10.9: No Power to Gas Resources
Washington
Power1- Preferred 14- Power 1-Preferred 14-
Resource to Gas Resource to Gas
160 Strategy Unavailable Straj Unavailable
Natural Gas 0 0 275 287
Solar 311 320 0 0
Wind 1,307 1,240 119 93
Energy Storage 261 549 0 0
Power to Gas 394 0 0 0
m Nuclear 100 222 0 0
Geothermal 20 20 0 0
Biomass 64 64 3 3
Demand Response 70 61 17 17
EE-Winter Capacity 156 156 49 49
EE- Summer Capacity 111 111 38 38
PVRR (Millions) $10,924 $11,020 $4,758 $4,772
2030 Rate ($/kWh) $0.130 $0.130 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.275 $0.180 $0.188
No Inflation Reduction Act (IRA)
This scenario shows how the resource portfolio and costs to the system would change if
the IRA was repealed, and it also shows the impact of the policy to the portfolio. This
analysis focuses on the resource impacts and does not estimate a change in the load
forecast or energy efficiency impacts of losing the IRA. It is likely the load forecast would
be lower due to less electrification of buildings.
Due to CETA and the CCA, the total amount of new renewable energy created is
unchanged. Overall, the only material change in the portfolio is Kettle Falls unit 2 is
removed and replaced with energy storage and a minimal amount of new renewable
energy. The change takes place when renewable energy is chosen and allocated to a
specific state. Without the IRA's Production Tax Credit, Idaho would not participate in any
new wind resources. Furthermore, the timing of new wind would also be delayed until the
resource needs of Washington's CETA requirements. As Avista anticipates it has already
met its near term CETA compliance requirements, new wind acquisition is minimal (100
MW in 2030 and 200 MW in 2035), while all remaining wind is beyond 2039.
The cost impact of this policy is more important to Washington than Idaho customers.
Washington would have 2.7% higher rates in 2045, and Idaho's rate increase is only
0.5%. Over the 20-year period, the system PVRR is 2.2% higher without the IRA. This
scenario highlights most of the early wind acquisitions are due to economic selection
rather than resource need. The need to acquire wind early will be dependent on the
economic outlook of the energy price compared to the market rather than focus on
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meeting renewable energy targets. This implies early acquisition of wind energy is
somewhat speculative and requires additional analysis beyond the IRP before adding
large amounts of wind energy that will likely need to be sold in the energy market until the
middle of the next decade.
Table 10.10: No IRA Impacts
Washington
Preferred Tax Preferred Tax
Resource Incentives Resource Incentives
Pftdl Strategy Strategy
Natural Gas 0 01 275 287
Solar 311 318 0 0
Wind 1,307 1,331 119 93
�, Energy Storage 261 297 0 0
io Power to Gas 394 394 0 0
m Nuclear 100 100 0 0
Geothermal 20 20 0 0
Biomass 64 7 3 3
Demand Response 70 73 17 17
EE-Winter Capacity 1 1561 156 49 49
EE-Summer Capacity 1111 111 381 38
PVRR(Millions) $10,924 $11,266 $4,758 $4,754
2030 Rate($/kWh) $0.130 $0.131 $0.112 $0.112
2045 Rate($/kWh) $0.248 $0.2551 $0.180 $0.181
500 MW Nuclear Energy
Between the PRS and many of the high load growth scenarios, nuclear energy is a
common resource selection to solve the resource deficits once other resource options
become limited or too expensive. One of the main concerns with nuclear energy is the
high cost and time necessary to develop the resource due to permitting and construction.
This scenario addresses what a portfolio would look like if 500 MW of nuclear energy is
added to the system in 2040. The analysis assumes the energy is split between Idaho
and Washington using the PT ratio and no other resources are retired.
The analysis indicates a significantly higher energy rate in 2045 for both Washington (9%)
and Idaho (30%). The cost change for this scenario is immaterial as Avista would not
endeavor a project this large unless its cost were recoverable and justified compared to
other resources. These cost increases illustrate why nuclear is not chosen in the PRS in
large amounts, but the 9% higher cost for Washington indicates it may be a viable
resource to meet clean energy needs if enough other clean resources are not developed.
The costs could be further reduced if the PTC for nuclear power is permanently extended.
As for Idaho, nuclear energy is at a significant premium compared to natural gas CTs and
wind energy.
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The resource portfolio with a large amount of nuclear energy undergoes significant
changes to reduce natural gas (-185 MW), solar (-300 MW), wind (-606 MW), energy
storage (-200 MW), biomass (-58 MW), and demand response (15 MW). Effectively the
500 MW nuclear facility satisfies the need for 1,364 MW of other resources as shown in
Table 10.11. Avista's reliability analysis also shows significantly less outage probability at
0.6%, effectively allowing for a lower PRM and could reduce costs.
Table 10.11: No Power to Gas Resource..
Washington
1- 11-Least 1- 11-Least
Preferred Cost+ 500 00
Resource MW Resource MW
Strategy Nuclear in Strategy Nuclear in
0-0 -0
Natural Gas 0 0 275 90
Solar 311 11 0 0
Wind 1,307 687 119 133
Energy Storage 261 61 0 0
Power to Gas 394 364 0 30
(b Nuclear 100 334 0 166
Geothermal 20 20 0 0
Biomass 64 7 3 3
Demand Response 70 55 17 17
EE-Winter Capacity 156 156 49 49
FEE-Summer Capacity 111 111 381 38
PVRR (Millions) $10,924 $11,697 $4,758 $5,124
2030 Rate($/kWh) $0.130 $0.131 $0.112 $0.111
2045 Rate($/kWh) $0.248 $0.270 $0.180 $0.234
Clean Energy Portfolio by 20W
This scenario studies a future where no new or existing natural gas generation serves
electric customers in either jurisdiction by 2045. This scenario meets Avista's clean
energy goal where all generation would be sourced from renewable or non-carbon
emitting sources by 2045101 In this future scenario, jurisdictional allocation issues
become less relevant as both states would have similar objectives by 2045. Avista found
when conducting a 2030 reliability analysis for this scenario, it failed to meet the 5% loss
of load probability threshold, and the PRM was increased to 26% for 2030 to ensure the
portfolio is reliable. In addition, the 24% PRM in 2045 LOLP is well below the 5%
threshold.
This clean energy portfolio shows significant energy rate increases for both states, even
though the resource strategy is similar for Washington. In Washington's case, the 2045
energy rates are 17% higher due to sharing more of the lower cost clean energy resources
10' Washington's Clean Energy Future (mvavista.com)
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to meet Idaho's energy needs. Idaho's 2045 energy rate is significantly higher at 56%
compared to the RPS. Its average energy rate in 2045 is $0.28 per kWh versus $0.18 per
kWh in the PRS. In exchange for the higher rates, greenhouse gas emissions fall from
0.55 million metric tons to zero. Over the 20 years, the levelized cost of GHG emissions
reduction between this scenario and the PRS is $220 per metric ton, but in 2045 the cost
increases to $1 ,230 per metric ton.
The major short-term change in this portfolio compared to the PRS is the elimination of
the natural gas CT in 2030. This capacity is replaced by increasing demand response
amounts and using Montana wind and energy storage to meet Idaho's deficits. The total
amount of wind acquired for this scenario by 2030 is effectively the same, only the
jurisdictional allocation changes. Given the minimal rate impact in 2030, the possibility of
not pursuing natural gas for Idaho customers could be a viable option to defer capacity
needs to a later time with minimal impact. Avista's RFP in 2025 should be able to validate
this approach. Replacing Idaho's share of the aging natural gas fleet and meeting new
load growth without using new natural gas poses a significant challenge without a low-
cost clean energy resource, but to achieve this objective, new nuclear energy is required.
The significant changes in resource strategy compared to the PRS are shown in Table
10.12, where significant increases in resources are needed to meet the resource deficits
post 2035. In this period, Idaho relies on a similar portfolio of resources to Washington's
PRS, with ammonia fired CTs, solar, wind, energy storage, and nuclear together meet
demand. In total, the portfolio requires the following additional resources compared to the
PRS: 62 MW solar, 130 MW of wind, 93 MW of energy storage, 384 MW of nuclear, and
58 MW of biomass, and 14 MW of energy efficiency to offset the 275 MW of lost natural
gas and 94 MW of hydrogen (associated with Coyote Springs 2).
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Table 10.12: 2045 Clean Resource Portfolio
Washington
P'"referre Resource Preferred Resource
LML�.
Natural Gas 0 0 275 0
Solar 311 333 0 40
Wind 1,307 1,058 119 498
U) Energy Storage 261 231 0 124
: Power to Gas 394 240 0 60
co Nuclear 100 318 0 166
Geothermal 20 20 0 0
Biomass 64 45 3 22
Demand Response 70 120 17 26
EE-Winter Capacity 156 168 49 49
EE- Summer Capacity 111 125 38 38
PVRR (Millions) $10,924 $11,135 $4,758 $4,873
2030 Rate ($/kWh) $0.130 $0.131 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.289 $0.180 $0.280
Other Portfolios
In addition to the load and resource changes, other scenarios were requested by either
state IRP rules, the TAC, or by Avista. These scenarios are used for developing avoided
costs, assisting in CETA targets for the CEIP, quantifying resource adequacy, and
understanding the impact to the portfolio should the CCA is repealed102. Below is a list of
the other portfolio scenarios.
• Alternative Lowest Reasonable Cost (#2)
• Baseline Least Cost (#4)
• Maximum Customer Benefits (#10)
• 17% PRM (#12)
• 30% PRM (#13)
• Minimal Viable CETA Targets (#15)
• Maximum Viable CETA Targets (#16)
• PRS Constrained by the 2% Cost Cap (#17)
• PRS w/ CCA Repealed (#26)
Counterfactual Studies
Avista creates two counterfactual studies for avoided cost development and for CETA
cost cap calculations for the 2025 CEIP. The Alternative Lowest Reasonable Cost
102 CCA was not repealed in the November 5, 2024 election.
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portfolio (#2) is designed to set the baseline cost for calculating the 2% cost cap for the
2026-2029 CEIP period. This scenario assumes CETA's clean energy targets, and the
Named Community Investment Fund (NCIF) do not exist, but it still requires the SCGHG
in resource selection.
The second counterfactual study, Baseline Portfolio (#3), is similar but also removes the
SCGHG and NEls from the resource decision making process. This portfolio is similar to
past IRPs where it solved for the least cost resource portfolio. The baseline scenario is
primarily used to estimate avoided costs as it sets the baseline for determining the cost
to meet energy and capacity, whereas the PRS stands in as the energy or clean energy
premium. Lastly, the baseline scenario demonstrates the cost premium to meet the
remaining clean energy goals for Washington from today's portfolio but does not quantify
the cost of the clean energy choices it has made prior to 2026.
The cost changes of the Alternative Lowest Reasonable Cost scenario are not relevant
to the IRP as they focus on the 2026-2029 period. In this case, the increased cost
between this scenario and the PRS is $4 million or less than 1%. This small change is the
result of less energy efficiency and not pursuing community solar. This portfolio will be
discussed further in the 2025 CEIP.
The Baseline Portfolio shows some interesting results, for instance the Clean Energy
Portfolio discussed above aligns the objectives of both states. In this case, Washington's
rates in 2045 would be 17.4% less by not pursuing CETA, translating into an implied
carbon reduction price of $71 per metric ton between 2026 and 2045. Most of the cost
increase and emissions reduction savings come in 2045, where the average cost of GHG
emission reduction is $341 per metric ton.
An interesting result of this study is that Idaho's energy rates slightly increase compared
to the PRS by 2.4% due to a shifting of resources to Washington by effectively requiring
Idaho customers to invest in energy storage, increasing rates compared to natural gas
CTs. The Baseline Portfolio primarily shifts capacity to natural gas resources and away
from P2G, solar, energy storage, biomass, and nuclear. Wind continues to be cost
effective, but less wind is obtained.
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Table 10.13: Counterfactual Scenarios
Washington
Preferred Aternative Portfolio Preferred Aternative Portfolio
Resource Lowest Resource Lowest
Strategy easonable Strategy Reasonable
Cost Cost
Lk Mil Portfolio =Am =I Portfoliol"
Natural Gas 0 66 535 275 298 266
Solar 311 100 0 0 0 0
Wind 1,307 894 367 119 66 453
4 Energy Storage 261 117 1 0 8 31
Power to Gas 394 364 60 0 30 30
Nuclear 100 0 0 0 0 0
Geothermal 20 20 0 0 0 0
Biomass 64 7 0 3 3 0
Demand Response 70 73 53 17 19 26
EE-Winter Capacity 156 148 156 491 51 49
EE- Summer Capacity 111 105 111 381 41 38
PVRR (Millions) $10,924 $10,796 $10,851 $4,758 $4,766 $4,655
2030 Rate($/kWh) $0.130 $0.130 $0.131 $0.112 $0.112 $0.111
2045 Rate($/kWh) $0.248 $0.208 $0.205 $0.180 $0.189 $0.185
Kebt,urce Adequacy Scenarios
As part of the TAC discussion regarding the near resource adequacy event in January
2024, the topic of what level of reliability utilities should plan for, absent a specific
requirement was considered. Further, with the creation of the Western Resource
Adequacy Program (WRAP), utilities could lower their individual PRM levels by
coordinating resources and adequacy methodologies. After this TAC discussion, it was
proposed to conduct two scenarios: 1) would emulate near zero LOLP (30% PRM), and
2) would estimate a future PRM where the WRAP is fully operational (17% PRM).
Effectively these scenarios require more capacity resources in the winter months for the
30% PRM and less for the 17% PRM. The result of the studies changed Idaho's resource
strategy to include more natural gas resources for the 30% PRM scenario and less for
the 17% PRM scenario. Washington obtains more energy storage in the 30% PRM
scenario and less in the 17% PRM scenario.
The energy rate and PVRR are most interesting for these two scenarios. On a PVRR
basis, the 17% PRM scenario lowers costs by $69 million or 0.4%, and illustrates the
benefits of the WRAP, if all utilities participate, in creating a reliable regional system. As
for the 30% PRM, increasing reliability targets increase cost by $182 million or 1.2%
PVRR. As shown in Table 10.14, this translates into a 1.7% increase to the 2045 energy
rate for Washington and a 1 .5% increase for Idaho. The results indicate a minimal cost
increase for higher levels of reliability, but further analysis should be undertaken to
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understand the benefits of greater reliability. Also, in higher load scenarios, it is still
possible higher reliability cases could increase rates at a more drastic rate.
cable 10.14.
Washington
Resource Resource
Strategy ___JlL Strategy --A
Natural Gas 0 01 0 275 213 300
Solar 311 210 311 0 105 0
Wind 1,307 1,308 1,315 119 123 125
Energy Storage 261 131 419 0 0 25
Power to Gas 394 394 394 0 0 0
m Nuclear 100 108 100 0 0 0
Geothermal 20 20 20 0 0 0
Biomass 64 64 64 3 3 3
Demand Response 70 73 73 17 17 17
EE-Winter Capacity 156 156 156 49 49 49
EE- Summer Capacity 111 111 111 38 38 38
PVRR (Millions) $10,924 $10,880 $11,083 $4,758 $4,734 $4,781
2030 Rate ($/kWh) $0.130 $0.130 $0.132 $0.112 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.244 $0.252 $0.180 $0.180 $0.183
Maximum Customer Benefits
Washington State's IRP rules require a scenario to estimate the impacts of maximizing
customer benefits. Avista proposed to model this scenario with the objective to improve
each of the Customer Benefit Indicators (CBIs) the IRP has an impact on (see the CEAP
for further information on CBIs). To do this, Avista made several changes to the capacity
expansion model including:
• Includes 164 MW of distribution solar and 38 MW energy storage over
the 20-year period. DER solar is designed to offset lower income
customer's costs.
• Prohibit the model from selecting air emitting resources, such as no
new biomass or power to gas CTs for Washington.
• Assumes the only new out of state resource to serve Washington
customers is 200 MW of Montana wind along with the associated
market resources from connecting the transmission line to the east.
• Increase the 10% Power Act adder for energy efficiency to 20% to
incent more energy efficiency.
• Assume Named Communities have the higher level of roof top solar
and electric vehicles from the DER Potential Study scenario where
Named Communities had equal DER penetration as other
communities.
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The changes made to this scenario result in an increase in both PVRR to Washington by
$264 million or 2.4%, although by 2045 the average energy rate is 12.7% higher as shown
in Table 10.15. The impacts to Idaho are negligible. The model changes resource
selection to include more solar (+284 MW), energy efficiency (+337 MW), nuclear (+189
MW), energy efficiency (+6 MW), and demand response (+50 MW). Reductions to the
resource strategy include removing the power to gas CTs, geothermal, and biomass.
Wind selection is 166 MW less. This scenario would require an immediate need for
building DER solar and energy storage every year going forward. For the most part, the
remaining resource changes are later in the IRP time horizon.
Table 10 Washingtr - Berafi+c-
Natural Gas 0 0 275 278
Solar 311 595 0 0
Wind 1,307 1,160 119 100
Energy Storage 261 598 0 0
i� Power to Gas 394 0 01 0
m Nuclear 100 289 0 0
Geothermal 20 0 0 0
Biomass 64 0 3 0
Demand Response 70 120 17 17
EE-Winter Capacity 156 161 49 50
EE- Summer Capacity 111 116 38 39
PVRR (Millions) $10,924 $11,188 $4,758 $4,767
2030 Rate ($/kWh) $0.130 $0.130 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.279 $0.180 $0.180
A summary of CBI metrics changes as compared to the PRS for 2045 is shown in Table
10.16. In this case, all CBIs improve, but some (i.e., customers with energy burden) do
not improve materially due to the added cost of the portfolio resource additions and the
requirement of additional subsidies from other customers to support the added cost.
Appendix G includes CBI results for all portfolios and for each year if further details are
needed.
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Table 10.16: 2045 Customer Benefits Indicator Results
Customer Benefit Indicator Measurement PRS Max Change
Customer
Benefits
#2a:WA Customers with Excess Energy Burden Customers 59,696 59,143 (553)
#2b: Percent of WA Customers with Excess Energy Burden % Customers 21.2% 21.0% -0.2%
#2c:Average Excess Energy Burden $ 1,998.3 1,801.6 (196.7)
#5a:Total MWh of DER<5MW in Named Communities MWh 185,973 574,875 388,902
#5b:Total MWh Capability of DER Storage<5MW in NC MW 2.4 306.4 304.0
#6:Approximate Low Income/NC Investment and Benefits Annual Investment($mill) 6.5 68.8 62.2
#6:Approximate Low Income/NC Investment and Benefits Annual Utility Benefits ($mill) 21.6 37.0 15.4
#6:Approximate Low Income/NC Investment and Benefits Annual NEI Benefits($mill) 38.4 35.5 (3.0)
#7: Energy Availability-Reserve Margin Winter% 20.0% 19.9% -0.1%
#7: Energy Availability-Reserve Margin Summer% 25.1% 28.2% 3.1%
#8: Generation in WA and/or Connected Transmission System %of Generation 82.0% 83.7% 1.7%
#9a: S02 Metric Tonnes - - -
#9b: NOx Metric Tonnes 0.0 0.0 (0.0)
#9c: Mercury Metric Tonnes 407.5 148.4 (259.1)
#9d:VOC Metric Tonnes 26.9 9.2 (17.6)
#10a: Greenhouse Gas Emissions Direct Emissions(metric tonnes) - -
#10a: Greenhouse Gas Emissions Net Emissions (metric tonnes) (0.2) (0.2) (0.0)
#10b: Regional Greenhouse Gas Emissions Metric Tonnes 8.8 8.8 (0.0)
CETA Targets
In the 2021 CEIP process, the CETA targets were discussed for the trajectory between
2022 and 2030. The 2022-2025 levels were approved at higher levels than Avista's
original proposal. This led to a condition of the approved CEIP to study an alternative
clean energy target. This requirement is documented as the 2021 CEIP Condition #33. In
this condition "Avista agrees to model a scenario in the 2025 Electric IRP meeting the
minimum level of primary compliance requirements beginning in 2030 that will create the
glide path to 2045. If the results of this modeling differ from the Company's PRS and
Clean Energy Action Plan, it must explain why." Avista is providing this scenario as #15,
the minimal viable CETA target scenario, and it is also conducting the counter to this
scenario by including the maximum viable CETA target scenario (#16). Table 10.17
includes the targets for primary compliance for these two scenarios compared to the PRS.
Table 10.17: CETA Target Scenarios
Period PRS Minimal Viable Maximum Viable
Primary Alternative Primary Alternative Primary Alternative
2026 66.0% 62.5% 70.0%
2027 69.5% 62.5% 73.0%
2028 73.0% 62.5% 75.0%
2029 76.5% 62.5% 78.0%
2030-33 80.0% 20.0% 80.0% 20.0% 81.8% 18.2%
2034-37 85.0% 15.0% 82.0% 18.0% 86.8% 13.2%
2038-41 90.0% 10.0% 88.0% 12.0% 92.2% 7.8%
2042-44 95.0% 5.0% 92.0% 8.0% 97.1% 2.9%
2045 100.0% 0.0% 100.0% 0.0% 100.0% 0.0%
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Chapter 10: Portfolio Scenario Analysis
For the minimal viable CETA target scenario, there is no change in the resource selection
and timing of resources until 2044. In this case the only change is less than 4 MW of
resource selection. The reason for no change in the resource selection is due to the 2030
and 2045 targets and the financial incentive to acquire resources early due to both pricing
and meeting capacity needs. With the IRP designed to achieve 100% clean energy in
2045 and acquire clean resources on a long-term basis without risk of disallowance, the
model design builds only renewable energy. With the 2045 CETA target requiring more
renewable energy than load, the model is incented to build resources to comply with 2045
goals. Even if the interim targets are lower, the model still sees the 2045 objective and
the physical energy and capacity needs required to be met with clean energy. If the 100%
target was moved from 2045 to 2050, the resource plan would possibly change in the
outer years of the plan.
Another reason for a lack of resource selection change when lowering targets is due to
the availability of resources today combined with those selected for acquisition exceeding
CETA targets due to economic viability or capacity needs. If this scenario was conducted
with either a lower market price forecast or without the IRA incentives, it is possible wind
resource additions could be delayed in a low target scenario. Further, the final use rules
could impact the results of these scenarios depending on how the utility must show
compliance with the clean energy standards or "use" rules.
In the maximum viable clean energy targets scenario (#16), the capacity expansion model
did not change from the PRS to meet the 100% goal in 2045 with only utilizing clean
energy resources to meet future resource needs. This lack of change is based on the
same reasons in the minimal viable scenario (#15). Lastly, there is an impact not modeled
in the IRP, but will be handled in the CEIP process. This issue is the quantification and
valuation of Renewable Energy Credits (RECs) or the ability to sell specified clean
power.103 If Avista has lower targets given its long clean energy position (as compared to
the targets), Avista could sell this excess generation to others, and it will lower customer
rates. Higher clean energy targets result in higher energy rates due to less opportunity of
sales.
PRS Constrained to the Cost Cap
The PRS analysis does not limit the cost of the portfolio to comply with CETA's 2% cost
cap, but rather demonstrates the costs and portfolio selection needed to comply with the
targets. The cost cap consideration will likely be conducted through the CEIP review
process after the four-year period. The IRP can be a good tool to estimate when a cost
cap is potentially going to be reached. In this and the prior IRP, Avista identified the 2045
resource section in the PRS is expected to be above the cost cap. The reason to exclude
103 The IRP does not include the Renewable Energy Certificate (REC) revenue a resource could earn if
sold on the market. This is due to the IRP not being developed to build resources for non-customer needs,
but rather quantify the value of resources needed for load. However, it does consider the benefits of selling
resources in the energy market when it is resource long.
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Chapter 10: Portfolio Scenario Analysis
the cost cap in the PRS is due to the Alternative Lowest Reasonable Cost (#2) portfolio
needing to be available for comparison. In this case, while the IRP analyzes this portfolio
scenario, the portfolio is onlyvalid forthe 2026-2029 CEIP period. It is not relevant beyond
this period, because the decisions in the CEIP will be included in the future "Alternative
Lowest Reasonable Cost" portfolio. The 2% cost cap builds on decisions previously made
to comply with CETA. The 2% cost cap is not applied to what rates would be absent
CETA, but rather 2% higher than what rates were last year considering decisions already
made to comply with CETA.
To address this cost cap scenario, an Alternative Lowest Reasonable Cost portfolio for
2045 must be made assuming the PRS resource selection for 2026 through 2043 are
made. Then the model solves for the resource needs without CETA targets in 2045. With
this information, a cost cap for 2045 is calculated by taking the 2044 cost and multiplying
it by 2% and then by four. The cost is multiplied by four to account for a 2045 through
2048 compliance period, although statute does not address compliance windows beyond
2044.
The model results of this scenario show the PRS exceeds the cost cap and different
resource decisions are made in 2045 as compared to the PRS. The results show the
Company will pursue less wind, energy storage, and nuclear while increasing solar and
P2G resources. The analysis also includes retaining Coyote Springs 2 beyond 2045 and
using hydrogen to fuel 30% of the plant. Idaho would be impacted by retaining Coyote
Springs 2 beyond 2045, and as it was assumed, Idaho would pick up this resource from
Washington customers. The total resource changes and costs are shown in Table 10.18.
The results lower the average energy rate for Washington customers by $0.02 per kWh
for a 9.3% decrease compared to the PRS. Although for Idaho there is a 3.5% increase
in average rate due to the need for new gas turbines.
Avista is not proposing to use this scenario as its PRS, but its intent is to highlight the
potential issue with compliance in 2045. Furthermore, clarification of compliance
mechanisms for 2045 will be needed to address how the cost cap will be treated after
2044. Avista may include the methodology for estimating the post 2044 cost cap in the
2027 IRP and only plan for what can be implemented in the cost increase range of the
statute and conduct the "capless" study as a scenario. Further, the 2027 IRP will model
years 2046 and 2047, and will show more future years with the 100% clean energy goal
to illustrate how the Company could comply with the goal given the cost constraint. Avista
has several hydroelectric contracts expiring at the end of 2045, thus creating a significant
resource need in 2046 if these contracts are not renewed.
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Table 10.18: CETA 2045 Cost Cap Scenario
Washington
Resource Constrained Resource Constrained
Strategy to 2%Cost Strategy to 2%Cost
ILW Cap Cap
Natural Gas 0 0 275 362
Solar 311 395 0 0
Wind 1,307 999 119 119
Energy Storage 261 232 0 0
Z5 Power to Gas 394 439 0 0
cz Nuclear 100 0 0 0
Geothermal 20 20 0 0
Biomass 64 7 3 3
Demand Response 70 73 17 17
EE-Winter Capacity 156 1561 49 49
EE- Summer Capacity 111 1111 38 38
PVRR (Millions) $10,924 $10,867 $4,758 $4,767
2030 Rate ($/kWh) $0.130 $0.130 $0.112 $0.112
2045 Rate ($/kWh) $0.248 $0.225 $0.180 $0.187
CCA Repealea
At the time of this drafting of this IRP, the Climate Commitment Act (CCA) is law in the
State of Washington. On November 5, 2024, voters rejected the initiative to repeal the
law. Since at the time of the draft IRP filing, Avista didn't not know the outcome of Initiative
2117, Avista conducted a simplified study to better understand the impact to the resource
plan if voters repealed CCA. The CCA has macro-economic impacts on energy prices in
the Northwest. The repealing of this law assumes a major change for this study and
conducts a new wholesale electric price forecast without the CCA (see Chapter 9). The
scenario results in lower wholesale electric prices. With lower market prices, the
economics of certain resources change, but the driver to acquire "clean" resources for
Washington State does not change due to the 100% clean energy goals in CETA.
Therefore, the impact on the plan is timing of renewable resource acquisition for
Washington and if the wind resources selected for Idaho in the PRS remain. If the CCA
was repealed, the timing of wind would be delayed, and fewer projects are likely to be
cost effective for Idaho customers.
Avista is not able to compare the cost of this portfolio to the PRS due to the unknown
nature of how the CCA's free allowances will be distributed to electric customers.
However, it is known that wholesale electric prices will fall, and this will lower the potential
revenue from selling excess clean energy resources to the market.
Table 10.19 outlines the change in resource selection without the CCA. For Idaho
customers, the amount of wind falls by 52 MW. For Washington, ending the CCA changes
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Chapter 10: Portfolio Scenario Analysis
resource selection, but it generally selects the same type of resources where solar,
energy storage, and nuclear are increased, but wind, and biomass generation decrease.
The first wind acquisition in the PRS is delayed from 2029 to 2030. The minimal impact
is due to CETA targeting the acquisition more than the overall market price of power.
Table 10.19: CCA Repealed Scenario
Washington
Resource Resource
Strategy Strategy
Natural Gas 0 0 275 273
Solar 311 319 0 0
Wind 1,307 1,294 119 66
Energy Storage 261 288 0 0
Power to Gas 394 394 0 0
Nuclear 100 134 0 0
Geothermal 20 20 0 0
Biomass 64 7 3 3
Demand Response 70 73 17 17
EE-Winter Capacity 156 156 49 49
EE- Summer Capacity 111 111 38 38
Reliability Analysis summary
Avista conducted reliability studies on specific scenarios to understand the impact to
reliability based on resource choices. Avista uses the same PRM and qualifying capacity
credits (QCC) for all scenarios. Avista's current reliability metric is to achieve at least a
5% LOLP to be reliable. A second metric is to be below 0.10 Loss of Load Expectation
(LOLE). The capacity expansion modeling requires a minimum of 24% planning margin
calculated by the total QCC of resources as compared to peak load. The result of the
capacity expansion modeling shows by 2045 the there is more QCC than needed in 2045.
Avista also provides other reliability metrics for informational purposes. The results of this
analysis (shown in Table 10.20) demonstrate the scenario portfolios generally result in
resource adequate systems and are below the 5% LOLP threshold. This is a result of the
PRM of the portfolios generally being higher than the minimum threshold. Although the
#12 scenario - 17% PRM, results in a 21.5% PRM in 2045 and a 4.7% LOLP. This
indicates Avista could be using a PRM of 21% to 22%, but a secondary indicator of LOLE
is higher than 0.1 and indicating a non-reliable portfolio with this metric. Overall, Avista's
24% PRM and associated QCC values seem reasonable considering both LOLP and
LOLE metrics. Although depending on the resource selection a lower PRM could be
justified, such as a future with high nuclear energy additions.
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Chapter 10: Portfolio Scenario Analysis
Table 10.20: Reliability Results
Year Actual Loss of Loss of Loss of Loss of Expected Expected
January Probability Expectation Selected Load Load Load Hours Load Unserved Unserved
PRM • •
(LOLEV) reserves without
LK reserves
#1-Preferred Resource 2030 29.6% 3.20% 0.072 0.7 0.176 114 107
Strategy 2045 28.6% 3.30% 0.093 1.1 0.304 172 116
#2-Alternative Lowest 2030 29.5% 2.70% 0.071 0.7 0.222 117 60
Reasonable Cost 2045 25.8% 1.40% 0.037 0.4 0.126 57 2
#3-Baseline 2045 25.9% 2.90% 0.046 0.3 0.071 47 38
#4-Clean Resource Portfolio 2030 27.8% 6.00% 0.194 2.1 0.435 359 339
2045 2045 25.8% 1.70% 0.025 0.1 0.051 18 16
#9-System Building and 2045 26.4% 1.10% 0.035 0.3 0.122 56 1
Transportation Electrification
#11-500 NNV Nuclear 2045 28.7% 0.60% 0.007 0.0 0.009 2 0
#12-17%Planning Reserve 2030 26.1% 4.50% 0.127 1.4 0.293 232 221
Margin 2045 21.5% 4.70% 0.103 0.9 0.260 149 145
#13-30%Planning Reserve 2030 34.8% 1.60% 0.034 0.5 0.115 81 80
Margin 2045 34.4% 0.80% 0.017 0.1 0.035 18 17
#14-Power to Gas 2045 25.9% 4.00 0 0.137 1.6 0.375 324 323
Unavailable
#18-Data Center 2030 26.3% 5.20% 0.132 1.4 1 0.323 1 261 256
#19-RCP 8.5 Load 2045 29.6% 4.60% 0.106 0.6 1 0.169 1 76 49
Cost & Rate Impact Summary
The preceding portfolio summary gave contextual changes to each portfolio. This section
provides tables and charts to summarize the results of the studies. Table 10.21 outlines
PVRRs for each of the 25 portfolios for each state, and the 2030 and 2045 average energy
rates per kWh. The yellow bar indicators show the cost or rate of the category is within
3% of the PRS value, the green arrow pointing up indicates the category exceeds a 3%
increase compared to the PRS, and the red arrow pointing down indicates a 3% or greater
reduction.
The costs of each portfolio are summarized by jurisdiction and sorted by total system cost
impact in Figure 10.2. The higher cost scenarios include higher loads or higher clean
energy objectives, while lower cost scenarios have less loads or renewables. The ranking
order does not reflect the additional load served by these scenarios, therefore Figures
10.3 and 10.4 show the ranking of the energy rates for 2030 and 2045, sorted by 2045
rates. The 2030 rates do not materially differ since most resource decisions occur after
2030.
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Chapter 10: Portfolio Scenario Analysis
Table 10.21: Jurisdiction Cost and Rate Summary
N O O LO O O I- V LO M O V O M W O O P I-- N N N
C ? CO _N a0 N CO (O 40 W N _N N a0 W CO _N M W 00 _W N W W CO _W _N
N Y O O O O O O O O O O O O O O O O O O O O O O O O O
2
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OM 1 N_ N_ _ N_ N_ 00 N_ N_ _ N_ _ N_ N_ N_ N_ N_ N_ N_ _M N N_ CO _N N_ N
N Y O O O O O O O O O O O O O O O O O O O O O O O CDO
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O Y O O M CDCDC) N C) O O O N N C) O
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Chapter 10: Portfolio Scenario Analysis
Figure 10.2: PVRR Summary
5-Low Economic Growth Loads $10,641 $15,352
3-Baseline Portfolio $10,851 ' $15,506 m WA-PVRR($Mill)
2-Alternative Lowest Reasonable Cost Portfolio $10,796 ' $15,562 .ID-PVRR($Mill)
12-17%PRIM $10,880 $15,614
TOTAL PVRR($Mill)
21-Regional Transmission not available $10,902 $15,620
17-PRS Constrained to 2%Cost Cap $10,867 $15,634
19-RCP 8.5 Weather $10,907 $15,659
25-Northeast Retires Late $10,922 $15,680
16-Maximum Viable CETA Target $10,923 $15,681
15-Minimal Viable CETA Target $10,923 $15,681
1-Preferred Resource Strategy $10,924 $15,682
22-Northeast Retires Early P $10,993 ' $15,768
14-Power to Gas Unavailable $11,020 $15,792
23-On-system wind limited to 200 MW ! $11,030 $15,811
13-30%PRIM $11,083J� $15,864
10-Maximum WA Customer Benefits $11,188 $15,956
4-Clean Resource Portfolio $11,135 $16,007
24-No IRA Tax Incentives $11,266 $16,019
6-High Economic Growth Loads $11,494 ' $16,458
7-WA Building Electrification $11,825 $16,617
18-Data Center in 2030 $11,794 $16,666
11-Least Cost+500 MW Nuclear in 2040 $11,697 $16,822
8-WA Building Electrification&High Trans.Electrification $12,374 ' $17,165
20-Building Electrification&High Trans.Electrification w/o NG w/_. $13,342 $19,283
9-Building Electrification&High Trans.Electrification w/o NG $13,295 $19,490
0 0 0 0 0 0
<» o 0 0 0 0
0 0 0 0 0
N O N O N
V3 fR V3 fA
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Chapter 10: Portfolio Scenario Analysis
Figure 10.3: Washington Energy Rate Comparison
3-Baseline Portfolio $0.205
$0.131
2-Alternative Lowest Reasonable Cost Portfolio $0.208
$0.130
17-PRS Constrained to 2%Cost Cap $0.225
$0.130
18-Data Center in 2030 $0.237
$0.131
5-Low Economic Growth Loads $0.242
$0.131
12-17%PRM $0.244
$0.130
19-RCP 8.5 Weather $0.248
$0.132
1-Preferred Resource Strategy $0.248
$0.130
25-Northeast Retires Late $0248
$0.130
16-Maximum Viable CETA Target $0.248
$0.130
15-Minimal Viable CETA Target $0.248
$0.130
22-Northeast Retires Early $0.250
$0.131
21-Regional Transmission not available $0.250
$0.130
13-30%PRM $0.252
$0.132
24-No IRA Tax Incentives $0.255
$0.131
23-On-system wind limited to 200 MW $0.256
$0.131
6-High Economic Growth Loads $0.262
$0.128
11-Least Cost+500 M W Nuclear in 2040 $0.270
$0.131
14-Power to Gas Unavailable $0.275
$0.130
8-WA Building Electrification&High Trans.Electrification $0.276
$0.130
7-WA Building Electrification $0278
$0.131
10-Maximum WA Customer Benefits $0.279
$0.130
4-Clean Resource Portfolio $0.289
$0.131
9-Building Electrification&High Trans.Electrification w/o NG $0.310
$0.131
20-Building Electrification&High Trans.Electrification w/o NG w/RCP $0.317
8.5 $0.132
$0.00 $0.05 $0.10 $0.15 $0.20 $0.25 $0.30 $0.35 $0.40
■WA 2045 Rate($/kWh) ■WA 2030 Rate($/kWh)
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Chapter 10: Portfolio Scenario Analysis
Figure 10.4: Idaho Energy Rate Comparison
6-High Economic Growth Loads $0.167
$0.109
12-17%PRM $0.180
$0.112
10-Maximum WA Customer Benefits $0.180
$0.112
1-Preferred Resource Strategy $0.180
$0.112
15-Minimal Viable CETA Target $0.180
$0.112
16-Maximum Viable CETA Target $0.180
$0.112
21-Regional Transmission not available $0.181
$0.112
22-Northeast Retires Early $0.181
$0.113
24-No IRA Tax Incentives $0.181
$0.112
23-On-system wind limited to 200 MW $0.181
$0.112
25-Northeast Retires Late $0.182
$0.112
19-RCP 8.5 Weather $0.182
$0.113
13-30%PRM $0.183
$0.112
7-WA Building Electrification $0.184
$0.112
3-Baseline Portfolio $0.185
$0.111
8-WA Building Electrification&High Trans.Electrification $0.185
$0.112
17-PRS Constrained to 2%Cost Cap $0.187
$0.112
18-Data Center in 2030 $0.187
$0.112
14-Power to Gas Unavailable $0.188
$0.112
5-Low Economic Growth Loads $0.189
$0.112
2-Alternative Lowest Reasonable Cost Portfolio $0.189
$0.112
20-Building Electrification&High Trans.Electrification w/o NG w/RCP 8.5 $0228
$0.112
11-Least Cost+500 M W Nuclear in 2040 $0.234
$0.111
9-Building Electrification&High Trans.Electrification w/o NG $0.245
$0.111
4-Clean Resource Portfolio $0.280
$0.112
$0.00 $0.05 $0.10 $0.15 $0.20 $0.25 $0.30 $0.35 $0.40
■ID 2045 Rate($/kWh) ■ID 2030 Rate($/kWh)
Market Risk Analysis
In addition to costs or energy rates, the IRP provides insights into the energy market risks
of the portfolios by showing how much of the portfolio selection is impacted by changes
in the wholesale electric market. Figure 10.5 compares the 2045 market risk to the PVRR
of the portfolio cost (excluding additional distribution costs for electrification scenarios).
The 2045 market risk used in this analysis is TailVar95 and is calculated by the 95t"
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Chapter 10: Portfolio Scenario Analysis
percentile of portfolio costs subtracting the average portfolio cost for 300 simulations. The
market risks included are from varying loads, natural gas prices, emission pricing, hydro
conditions, and wind conditions. The portfolios with greater risk typically have a higher
dependance on either natural gas resources, market power purchases, or added load.
The only portfolios reducing market risk for Idaho are those investing in additional
renewable energy resources. As shown below, the lower risk comes at an added cost to
the system. For example, in the #4 Clean Portfolio by 2045 scenario, the extreme market
risk is $43 million or 48% lower, but the incremental cost to Idaho customers in 2045 is
$356 million, reflecting a $0.10 per kWh premium or 55% higher.
Figure 10.5: System Cost versus Risk Comparison
$180
$160
$140 •3
$120
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$1,200 $1,300 $1,400 $1,500 $1,600 $1,700 $1,800
Levelized Revenue Requirement Millions
Another metric used to evaluate portfolio risk combines the PVRR and Tail-Var95 values.
This is done by summing the levelized PVRR and levelized Tail-Var95. The results shown
in Figure 10.6 are sorted from the highest total cost to the lowest cost. Due to most of the
resource acquisitions occurring toward the end of the plan and the differing amounts of
load included in each of the portfolios, this metric is not as informative for scenarios with
differing loads. Figure 10.7 was created for 2045 to address these concerns. In this case,
the total cost of the year is divided by the energy sales to estimate an average energy
rate, then the TailVar95 risk value is added. The values shown in this figure are in cents
per kWh. This methodology demonstrates each of the scenarios on a more equal footing.
In this view, the risk additions compared to the total costs are low due to the overall size
of the rate base of the total utility cost. In addition, most of the resources serving load
have volumetric risk rather than natural gas price risk, except for the Idaho portion of load.
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Chapter 10: Portfolio Scenario Analysis
Figure 10.6: Portfolio PVRR with Risk Analysis
5-Low Economic Growth Loads 46$1,360
3-Baseline Portfolio $1,380
2-Alternative Lowest Reasonable Cost Portfolio $1,381
12-17%PRM $1,382
21-Regional Transmission not available 7$1,383
17-PRS Constrained to 2%Cost Cap 48$1,386
19-RCP 8.5 Weather 48$1,387
25-Northeast Retires Late 47$1,388
1-Preferred Resource Strategy $48$1,389
16-Maximum Viable CETA Target $48$1,390
15-Minimal Viable CETA Target 8$1,390
22-Northeast Retires Early $1,392
14-Power to Gas Unavailable $1,400
13-30%PRIM $46$1,403
23-On-system wind limited to 200 MW $52$1,405
4-Clean Resource Portfolio 138$1,407
10-Maximum WA Customer Benefits $1,412
24-No IRA Tax Incentives $60$1,431
6-High Economic Growth Loads $56$1,464
7-WA Building Electrification $51 $1,473
11-Least Cost+500 MW Nuclear in 2040 $41$1,480
18-Data Center in 2030 $58$1,484
8-WA Building Electrification&High Trans.Electrificatio 1$1,520
20-Building Electrification&High Trans.Electrification w/o NG w/RCP 8.5 $1,687
9-Building Electrification&High Trans.Electrification w/o NG $1,705
- 500 1,000 1,500 2,000
■System Levelized PVRR($Mill) ■Levelized Tail Risk($Mill) Total
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Chapter 10: Portfolio Scenario Analysis
Figure 10.7: 2045 System Energy Cost with Risk
2-Alternative Lowest Reasonable Cost Portfolio 24.25
3-Baseline Portfolio 24.28
5-Low Economic Growth Loads 25.03
17-PRS Constrained to 2%Cost Cap 25.39
12-17%PRIM 26.63
19-RCP 8.5 Weather 26.98
1-Preferred Resource Strategy 26.10 27.00
16-Maximum Viable CETA Target 26.11 27.02
15-Minimal Viable CETA Target 26.11 27.02
25-Northeast Retires Late 26.15 27.04
22-Northeast Retires Early 26.28 27.13
21-Regional Transmission not available 26.33 27.24
13-30%PRIM 26.53 27.45
24-No IRA Tax Incentives 26.66 i 27.65
23-On-system wind limited to 200 MW 26.77 27.72
18-Data Center in 2030 26.58 ' 27.53
10-Maximum WA Customer Benefits 28.72 29.68
14-Power to Gas Unavailable 28.54 29.48
11-Least Cost+500 MW Nuclear in 2040 29.81 30.43
6-High Economic Growth Loads 29.96 31.02
7-WA Building Electrification 30.28 31.37
8-WA Building Electrification&High Trans.Electrification 30.69 31.91
4-Clean Resource Portfolio 33.00 33.46
20-Building Electrification&High Trans.Electrification w/o NG w/RCP 8.5 37.81 38.49
9-Building Electrification&High Trans.Electrification w/o NG 38. 38.78
- 5 10 15 20 25 30 35 40 45
■Revenue Requirement 0TailVar95 Total Cents per kWh
Greenhouse Gas Emission Comparison
All resource strategies going forward will have GHG emission reductions compared to
current emissions. The reductions are largely due to Colstrip Units 3 & 4 leaving the
system at the end of 2025. Further reductions will be from reduced dispatch of existing
natural gas facilities due to Washington's CCA and Lancaster's PPA ending in 2041.
While each portfolio has GHG reductions, the reduced amounts are not all equal. Each
portfolio's 20-year reduction levels are shown in Figure 10.8. The data used for this chart
display gross emissions from Avista's existing and controlled generating resources in blue
and the green bars represent the net emissions when there are sales or purchases in the
wholesale energy market. Market transactions include an emissions rate factor of 0.437
metric tons per MWh as defined by the CCA, while market sales use the estimated
emission intensity of the Avista facilities.
The #4 Clean Portfolio by 2045 has the greatest GHG reduction levels using both metrics
and the #3 Baseline Portfolio has the least reduction on a gross level. It is worth noting
the 0.437 metric ton per MWh intensity rate is an incremental rate and likely does not
represent the average emission intensity rate of market purchases especially as the
system decarbonizes.
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Chapter 10: Portfolio Scenario Analysis
Figure 10.8: Emission Reduction (Millions of Metric Tons (2045 compared to 2026)
3-Baseline Portfolio
17-PRS Constrained to 2%Cost Cap '
1
6-High Economic Growth Loads •r
1
2-Alternative Lowest Reasonable Cost Portfolio
18-Data Center in 2030
21-Regional Transmission not available
13-30%PRM
7-WA Building Electrification
24-No IRA Tax Incentives
1
23-On-system wind limited to 200 MW
8-WA Building Electrification&High Trans.Electrification
10-Maximum WA Customer Benefits
5-Low Economic Growth Loads
1
15-Minimal Viable CETA Target '
16-Maximum Viable CETA Target
1-Preferred Resource Strategy
1
14-Power to Gas Unavailable
1
25-Northeast Retires Late
22-Northeast Retires Early
19-RCP 8.5 Weather
12-17%PRM
11-Least Cost+500 MW Nuclear in 2040
20-Building Electrification&High Trans.Electrification w/o NG w/RCP 8.5
9-Building Electrification&High Trans.Electrification w/o NG
4-Clean Resource Portfolio
-0.5 0.0 0.5 1.0 1.5 2.0
■Net Emission Change(MMT)
■Generation Emissions Change(MMT)
The second metric for evaluating GHG emissions regards the cost and emission
reductions compared to the PRS. Figure 10.9 shows the added PVRR cost compared to
the PRS and to the total GHG emission changes over the 20-year study horizon. The
emission quantification used is derived from gross emissions generated from Avista
controlled facilities. For example, the #18 scenario, the 200 MW Data Center, increases
cost by $983 million PVRR over the PRS and the GHG emissions are 2.4 million metric
tonnes higher than the PRS. Portfolios in the bottom left quadrant have lower costs and
lower GHG emissions compared to the PRS.
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Chapter 10: Portfolio Scenario Analysis
Figure 10.9: Change in Emissions Compared to Portfolio PVRR
5,000
4,000
• 9
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O
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Change in 20yr Total Greenhouse Gas Emissions (MMT)
Market Price Sensitivities
This IRP considers three alternative market price sensitivities to understand the impact
on the portfolio choices. These market sensitives are discussed in Chapter 9 and in Table
10.22 below and include the specific assumption changes and the resulting market price
effects. This section shows how portfolios with different resource selections perform in
these future market scenarios. Avista only studied the market impacts for the low and
high natural gas price scenarios against four portfolios. Avista did not study the impacts
of the portfolio without the CCA due to the difficulty in accounting for emission allowances
in the CCA program.
The first analysis represented in Table 10.22 shows the impact to natural gas pricing in
the four resource portfolio scenarios including the PRS, Baseline, Clean Resource, and
the nuclear scenarios. These portfolios were selected because they would show the most
impact to natural gas pricing based upon their portfolio's resource selection. The results
show portfolios with higher natural gas resources have higher overall costs due to natural
gas pricing as well as the opposite when prices fall. The total sensitivity of gas prices to
total portfolio costs over 20 years is small due to the small amount of electric utility cost
influenced by natural gas pricing. Furthermore, depending on the year, higher natural gas
prices could benefit the utility if the utility has excess energy to sell on the market. The
results of this study are over the 20-year period.
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Chapter 10: Portfolio Scenario Analysis
Table 10.22: Jurisdiction PVRR Sensitivity Analysis
WashingtonChange in PVRR vs Expected Case Market Pricing
High NG LowNG HighNGj wNG High Low
rices Prices Prices Prices NG Prices
M[FPortfol' &Mb 111m_ Prices
1- Preferred Resource Strategy 0.8% -0.1% 3.1% -1.7% 1.5% -0.6%
3- Baseline Portfolio 2.1% -0.9% 1.3% -0.6% 1.8% -0.8%
4-Clean Resource Portfolio 1.0% -0.2% 0.3% -0.1% 0.9% -0.2%
11- Least Cost+ 500 MW Nuclear in 2040 0.7% -0.1% 0.9% -0.4% 1.1% -0.4%
The second analysis shown in Table 10.23 shows the changes in GHG emissions. The
top half of the table shows how the portfolio's total emissions change over the 20 years
depending on natural gas pricing. High gas prices reduce the demand for natural gas
generation and thus lower emissions, whereas low natural gas prices increase natural
gas generation dispatch increasing emissions. The bottom half of this table shows how
the change in emissions compare to the PRS, where the#4 Clean Resource Portfolio has
the biggest GHG emission change compared to the PRS due to it removing and excluding
natural gas resources.
Table 10.23: PVRR and Emission Changes
Total GHG
Emissions vs
Expected Prices
High NG Low NG
111111111111111jJ& Prices___Eric
1- Preferred Resource Strategy -13.0% 7.7%
3- Baseline Portfolio -14.0% 8.8%
4- Clean Resource Portfolio -9.4% 5.7%
11- Least Cost+ 500 MW Nuclear in 2040 -11.8% 6.8%
TotaMHG
Emissions vs PIRS
j1h Portfolio
3- Baseline Portfolio -2.3% -0.1%
4- Clean Resource Portfolio -9.4% -14.6%
11- Least Cost+ 500 MW Nuclear in 2040 -1.8% -4.0%
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Chapter 10: Portfolio Scenario Analysis
Table 10.24: Portfolio #1: Preferred Resource Strategy
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Chapter 10: Portfolio Scenario Analysis
Table 10.25: Portfolio #2: Alternative Lowest Reasonable Cost
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Chapter 10: Portfolio Scenario Analysis
Table 10.26: Portfolio #3: Baseline
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Avista Corp 2025 Electric IRP 295

Chapter 10: Portfolio Scenario Analysis
able 10.27: Portfolio #4: Clean Resource Portfolio
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Avista Corp 2025 Electric IRP 296

Chapter 10: Portfolio Scenario Analysis
Table 10.28: Portfolio #5: Low Load Forecast
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Avista Corp 2025 Electric IRP 297

Chapter 10: Portfolio Scenario Analysis
Table 10.29: Portfolio #6: High Load Forecast
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Chapter 10: Portfolio Scenario Analysis
Table 10.30: Portfolio #7: Washington Building Electrification
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Chapter 10: Portfolio Scenario Analysis
Table 10.31: Portfolio #8: WA Building and Transportation Electrification
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Avista Corp 2025 Electric IRP 300

Chapter 10: Portfolio Scenario Analysis
Table 10.32: Portfolio #9: System Building and Transportation Electrification
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Avista Corp 2025 Electric IRP 301

Chapter 10: Portfolio Scenario Analysis
Table 10.33: Portfolio #10: Washington Max Customer Benefits
,- d MN7 oom in r% r <om ro I, ao am wm
of ae vi {u�ui Vm r�� on o • oeu rn v�i nm
fOV O N N N th O f• �N M r N N�
N P9
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Avista Corp 2025 Electric IRP 302

Chapter 10: Portfolio Scenario Analysis
Table 10.34: Portfolio #11: 500 MW of Nuclear in 204u
•V M 1p O N O M N eD V l�M IG V r a N N 1l ro N EO N OI
blNH.lOV V N IG CN'f lV 0 001 fD M N Hl C fG V W N
. M m E n N O
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i 0 IV - O �f0�
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i G G I!)
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Avista Corp 2025 Electric IRP 303

Chapter 10: Portfolio Scenario Analysis
Table 10.35: Portfolio #12: 17% PRM
a o n q roq D o o y My o t M(n o m N 7 yyN N n ro a t co a
• O O • O lNV • lOV Of O • t0 N fV O ' • lOV O • M N 10 n A
M
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O M V W N fD O 1y M lD OI
. Di Np TtG O n N O
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O N O OJ N Ol N M a s W N V
N N
N IG O V V
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N N M
i 0 O N O lMlyy (M�y n V
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Avista Corp 2025 Electric IRP 304

Chapter 10: Portfolio Scenario Analysis
Table 10.36: Portfolio #13: 30% PRM
a O m O y Ili a Ma O a M n m m 0 rn O N n m m O m rn
Omi • O r r • M N N N T O • f0 H N C O O • N • • N � � M c m n m �W A
N O!'
O O m A O M m N N O h
O N O Oml N N fwp m n N O
N m m
O N N m W N M N m n N 0
N M
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W
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V m m m N OI
n O O N 7 m
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m N N N O
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m m m 0 m
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G T111 I V V f] 61.61
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Avista Corp 2025 Electric IRP 305

Chapter 10: Portfolio Scenario Analysis
Table 10.37: Portfolio #14: Power to Gas Unavailable
v oao Mlfi Co prp��pMp��o av or r m7 a Nr u! r O - m m
O O N N M • Yf Q M N ' ' 10 M N O O M . n . . M O W�W W N W
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W Ol O N O O N r m N y r
N N E l0 N f0 � N r N O
O O 0 OOp � OI M M N M l0 OJ
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Avista Corp 2025 Electric IRP 306

Chapter 10: Portfolio Scenario Analysis
'able 10.38: Portfolio #15: Minimum CETA Target
C O N 1A O M O y M O VV W f�O b♦ V N f�W V a N 7 M O�
• O tO+1 M • y • �N Of� • �Y N N o N • N • • !1 O fG a Of anD N�
N N
0 0 0 O M Op�I N N O V h 7
O O M W N f�0 l0 M M r r N O
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aD N O N N <p 1p� M tp W
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Avista Corp 2025 Electric IRP 307

Chapter 10: Portfolio Scenario Analysis
able 10.39: Portfolio #16: Maximum CETA Target
v oM op 'It oMo yyro rr o loa a Nnma {a{yr� 7co a
N N
0 0 fG M O M V R N N R O h 7
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Avista Corp 2025 Electric IRP 308

Chapter 10: Portfolio Scenario Analysis
Table 10.40: Portfolio #17: PRS Cost Cap Constrained
v oo-n cop ooreop Nnao a r�mpp m m
C • 01 • V N M[S • IG tV o • N • .G.9 1 �N M
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Avista Corp 2025 Electric IRP 309

Chapter 10: Portfolio Scenario Analysis
Table 10.41: Portfolio #18: Data Center Load (200 MW in 2030)
• a ao 0a Op rOMO ayMp lr apol 1CN Nr R a r my
• M ' w�t0 • In • r N W M • ip N N Q O M • •
M M
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G M OJ lG 0 - . M O M fG W lG
N N
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Avista Corp 2025 Electric IRP 310

Chapter 10: Portfolio Scenario Analysis
Table 10.42: Portfolio #19: RCP 8.5 Temperatures for Load
V I�N Oi N O W O a Ma 4) q m r O IG M M N N r%W N YI M O.
' �M 17 • Y N N N T N � fC�Cl N o� • t+l • • Oi • th
lV N lV N
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Avista Corp 2025 Electric IRP 311

Chapter 10: Portfolio Scenario Analysis
Table 10.43: Portfolio #20: System Bldg & Transportation Electrification- RCP 8.5
V Ol N Yg
r CD M p Vp A p Mp 11 M 10 N 111 O 01 10 pM O 10 O A N V 10 T CD 0)
IqG O • O • W Q 1 O O N 001 O EMD Y!'A COD 10 N yy pp!�CO M M ;I A
NCD M N 01 1D 1M , N i0 W W tOD W
N �V
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f0 N N � N Q O M fOD
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N N
N M V
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W O N N m M O I IMO N W 1n V
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1n M 1n N to 1{NRD 1CpD O
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Avista Corp 2025 Electric IRP 312

Chapter 10: Portfolio Scenario Analysis
Table 10.44: Portfolio #21: No Regional Transmission
Oropf n ro o In O M p Nf Va a r r ro A n N r N M O M c I
' O H lN�l • V N�fOV V Rf • �O�N m � M • y • • � • • t+l C aD N� W N�tV Of fV N !1
W O O N O M 10 01 O O cI O 1�
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M O cI Y"i N pVp M tD OI
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Avista Corp 2025 Electric IRP 313

Chapter 10: Portfolio Scenario Analysis
Table 10.45: Portfolio #22: Retire Northeast in 2026
N N
O m m O M m pN O O N V h 7
N O O tW0 N r m O O r N O
N Yf YYff
oc� a W m m mm a
!1 fV N W
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N N
our m ry
C V O N m m 1p N W
N N O N m 0
m N m
m V r
O O �;G2 I:
M m m M m W m
W W
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v�m
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O O O V V N
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Cmm1
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om m g 0 S � N 191 N n t'+J
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m m V N N m N m W
tO .O cD
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Avista Corp 2025 Electric IRP 314

Chapter 10: Portfolio Scenario Analysis
Table 10.46: Portfolio #23: 200 MW Wind Limit
v rfgqo0 O O yMO as n(n ee en Ir Nnro aoa �Oow
' M Q M ' N • N oOV Of t0 N N COM! O N • V • . M O fC V IMO W N
M 01 N
h N 0 M l0 O O O a O V h
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o In o m v a ao u�a
O G G M - {V N M 00
h N OI
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cl 1l V IC
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N N t+f
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N N - tH Oi cV tH
M� N
C V O CD cp h W N M r tD O
fV V OI M� N
O M W yOy taRa CD N M VN
o Oo ro ao m rr
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(ti t0 N
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Avista Corp 2025 Electric IRP 315

Chapter 10: Portfolio Scenario Analysis
Table 10.47: Portfolio #24: No IRA Tax Incentives
v,00ro �R aoMo roMn W <en Nrn in o W eq W
m 000ae �u 000 euo�ei O ad m . eio ado aims
O M V N N O 1p M W N h W h
�M
N N
O O h O 1My
N Y! Yf
O 1�W O Op N N N V M fp W
V V
0 0�c o in m in a
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Chapter 10: Portfolio Scenario Analysis
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Chapter 10: Portfolio Scenario Analysis
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Chapter 11: Action Items
11 . Action Items
The IRP continues to be an iterative and collaborative process balancing regular
publication timelines while pursuing the best resource strategy for the future as the
market, laws, and customer needs evolve. The biennial publication date provides
opportunities to document ongoing improvements to the modeling and forecasting
procedures and tools, as well as enhance the process with new research as the planning
and regulatory environment changes. This section provides an overview of the progress
made on the 2023 Action Items and details the 2025 IRP Action Items for the 2027 IRP.
2023 IRP Action Items
• Incorporate the results of the DER potential study where appropriate
for resource planning and load forecasting.
The DER potential study included a spatial forecast of electric vehicles and customer
owned generation. The study results for additional load and load reductions were
included in the long-term load forecast used for resource selection within this IRP. The
DER potential study is available in Appendix F.
• Finalize the Variable Energy Resource (VER) study. This study
outlines the required reserves and cost of this energy type. Results of
this study will be available for use in the 2025 IRP.
Avista hired Energy Strategies to develop an estimate for capacity reserves to be held
by the utility for differing levels of VERs such as wind and solar. With these reserve
estimates, Avista was able to calculate the incremental cost of holding these reserves.
Furthermore, the reserves were also considered in the capacity planning of the system.
Additional information about this study can be found in Chapter 5. The analysis
concludes a cost of$0.15 to $0.19 per kW-month to integrate existing VER variability
on the system, the study evaluated future portfolios with up to 2,500 MW of new wind
and/or solar.
• Study alternative load forecasting methods, including end use load
forecast considering future customer decisions on electrification.
Avista expects this Action Item will require the help of a third-party.
Further, studies shall continue the range in potential outcomes.
For this IRP, Avista utilized Applied Energy Group's (AEG) end use model to
estimate future loads. This methodology is critical for modeling potential
electrification and efficiency improvements over time. The study was used for the
load forecast between 2030 and 2045. This was a drastic modeling change
compared to previous methods, highlighting many issues to address in future
forecasts, such as weather normalization and how to merge short-term versus
long-term forecasting methodologies and incorporating end uses to better estimate
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Chapter 11: Action Items
impacts of building electrification. Avista will perform a plus delta review to improve
and build upon for the next load forecast.
• Investigate the potential use of PLEXOS for portfolio optimization,
transmission, and resource valuation in future IRPs.
Avista acquired PLEXOS to test its viability for use in long-term planning. Avista
conducted a back-cast to validate performance of the tool. The back-cast found
the PLEXOS model can sufficiently model Avista's system and has capabilities
other models do not have, such as a more detailed hydro modeling capability.
Avista found the tool could be used for resource planning including resource
evaluation, capacity planning, and resource adequacy testing. The PLEXOS
software comes at the expense of lost customization, added license fees, and
additional employee time versus Avista's current modeling methodology. Avista
chose not to use PLEXOS during the 2025 IRP for any analysis due to these
factors and will continue to use Aurora and internally developed tools for the 2027
IRP.
• Continue to work with the Western Power Pool's WRAP process to
develop both Qualifying Capacity Credits (QCC) and Planning
Reserve Margins (PRM) for use in resource planning.
Avista continues to participate in the Western Power Pool's WRAP and continues
to include the QCC estimates in this IRP. As the program develops and more
information comes from the various studies conducted by Southwest Power Pool
(SPP), Avista will follow the progress and incorporate study results as appropriate.
In addition, Avista is participating in a regional study performed by E3 where it will
simulate regional resource needs to comply with the 100% clean energy goals.
Between the WRAP and this regional study, Avista should have QCC for future
IRPs.
• Evaluate long-duration storage opportunities and technologies,
including pumped hydro, iron-oxide, hydrogen, ammonia storage, and
any other promising technology.
Generic long-duration storage opportunities and technologies were included in this
plan as resource options, a discussion of technologies included and can be found
in Chapter 7. Avista will continue to participate in webinars, consultations with
vendors and developers, and participate in other educational forums to follow
developments in long duration storage technologies as they develop. Furthermore,
Avista anticipates gaining additional information on storage and other related
technology specific to our service territory as part of the 2025 all source RFP.
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Chapter 11: Action Items
• Determine if the Company can estimate energy efficiency for Named
Communities versus low-income.
Avista met with its energy efficiency consultant to understand the requirements for
dividing energy efficiency savings potential by geographic area. Conducting such
a study will require significant data currently not available for individual
neighborhoods. Given the expense of developing useful estimates, Avista
recommends keeping the current methodology by estimating the low income share
of total energy efficiency potential and using these values as a proxy for Named
Community potential. Avista still commits to exploring alternative means to
estimate energy efficiency on the local level. One option, discussed in Chapter 6,
is to validate if energy efficiency could offset the need for system improvements in
specific communities when a potential distribution constraint may exist in the
future.
• Study transmission access required to access energy markets as
surplus clean energy resources are developed.
As mentioned in Chapter 2 and Chapter 8 of this plan, Avista has an opportunity
to explore access to new markets such as Midcontinent Independent System
Operator (MISO) and SPP, along with adding capability to southern Idaho
resources via upgrading the Lolo - Oxbow line. Avista will continue to evaluate the
cost and benefit of these opportunities. Further information regarding transmission
can be found in Appendix D.
• Further discuss planning requirements for Washington's 2045 100%
clean energy goals.
Avista is awaiting final rules for the Clean Energy Transformation Act(CETA) as it
relates to the "use" of clean energy. Until final rules are approved, Avista is
planning its system to generate enough clean energy on a monthly basis to cover
Washington load (including losses). Furthermore, the Company is including an
hourly analysis based on dispatch of resources in future markets and if the markets
do not exist, to identify if it can meet load on an hourly basis in Chapter 2. Another
issue regarding the 100% clean energy goal is related to the cost cap and how it
will be applied.
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Chapter 11: Action Items
2025 IRP Action Items
To prepare for the 2027 IRP planning process, the 2025 Action Plan considers input from
Commission Staff, Avista's management team, and members of the IRP Technical
Advisory Committee (TAC) regarding additional analysis and further development of
projects for inclusion. These action items include both Company actions related to results
of this plan and planning items to enhance the 2027 IRP.
Company Actions
• Determine the Northeast CTs retirement date and develop a plan for
replacing the lost capacity.
• Pursue transmission expansion opportunities within Avista's service
territory and those connecting to Avista's transmission system.
• Develop an all-source Request for Proposal (RFP) in 2025 for the new
resources needed to meet future capacity deficiencies and determine
if the renewable energy identified in the PRS is cost effective. The
RFP will request proposals for demand response opportunities.
• Investigate options to increase natural gas availability and resiliency
for existing and potential new natural gas generation without additional
natural gas pipelines.
IRP Planning Actions
• Incorporate future policy requirements regarding CETA and/or the
Climate Commitment Act (CCA) implementation as directed by the
Washington Commission, legislature, or voter initiatives.
• Explore how end use load forecasting should or should not be included
in the 2027 plan by reviewing lessons learned from the new load
forecast process completed in the 2025 IRP.
• Consider an Integrated System Plan methodology coordinating
resource, transmission, and distribution planning to ensure lowest cost
plan for both natural gas and electric customers
• Work with the TAC to determine the best strategy for engagement,
such as meeting frequency (as experimented in this IRP), along with
best available technologies to facilitate communication and data
availability.
• Determine Avista's resource need impact of new generation and/or
loads within Avista's balancing authority not associated with Avista's
load service.
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Chapter 11: Action Items
• Incorporate any new Customer Benefit Indicators (CBIs), targets, or
directives from the 2025 Clean Energy Implementation Plan (CEIP).
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Washington Clean Energy Action Plan
Introduction
Avista's 10-year Clean Energy Action Plan (CEAP) is the lowest reasonable cost plan of
resource acquisition given societal costs, clean energy, and reliability requirement targets
over the IRP's 20-year time horizon, including known information and assumptions
regarding the future. Avista developed this CEAP in conjunction with its IRP Technical
Advisory Committee (TAC) to meet the capacity, energy, and clean energy needs of both
Idaho and Washington. The resources described in this CEAP are specific to
Washington's portion of Avista's system needs for compliance with the Clean Energy
Transformation Act (CETA). This plan describes how Avista will meet the key
considerations required by the Washington Utilities and Transportation Commission
(UTC). Details regarding the methodology and assumptions for this plan are included in
the 2025 IRP. This CEAP is the basis for the 2025 Clean Energy Implementation Plan
(CEIP). Table 1104 illustrates annual resource additions, including demand response (DR)
and energy efficiency, for 2026 through 2035.
Table 1: Resource Acquisition Forecast
Supply Resources(MW)
Washington Allocated Wind - - - 200.0 200.0 100.0 - - - -
System Allocated Wind(WA share) - - - - 65.9 66.0 103.8 - -
Distributed Solar 0.5 0.6 0.6 0.7 0.8 0.8 1.0 0.5 0.5
Total Resources 0.5 0.6 200.6 200.7 166.7 66.8 104.8 0.5 0.5
Cumulative Demand Response (MW)
Battery Energy Storage 0.0 0.1 0.2 0.9 2.5 3.4 3.8 4.3 4.8 5.4
EV Time of Use Rates 0.1 0.3 0.5 0.8 1.1 1.4 1.7 2.0 2.4 2.8
Variable Peak Pricing 0.3 1.0 2.2 3.2 3.7 3.9 3.9 3.9 3.9 3.9
Peak Time Rebate - - - - - - - - - 0.2
Total Demand Response 0.5 1.4 3.0 4.9 7.2 8.7 9.41 10.2 11.1 12.4
Cumulative Energy Efficiency
Energy Savings(aMW) 4.2 8.4 12.6 16.8 21.0 25.2 29.4 33.6 37.8 42.1
Winter Peak Reduction(MW) 8.5 17.0 25.6 34.1 42.6 51.1 59.7 68.2 76.7 85.2
Summer Peak Reduction(MW) 7.1 14.21 21.3 28.41 35.5 42.6 49.6 56.71 63.8 70.9
104 Energy efficiency savings totals 44.5 aMW when considering savings from line losses.
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Avista proposes annually increasing its clean energy target until the 2030 greenhouse
gas (GHG) emissions neutral target and then continuing the trajectory adding more clean
resources each year toward the 2045 target of 100% clean energy. Table 2 shows
proposed target percentages, starting with a 66% clean energy target in 2026 and
increasing to 76.5% by 2029, the last year of the 2025 CEIP. The table shows Avista can
meet the targets on an annual basis with existing Washington allocated resources through
2033. Attaining clean energy goals beyond 2033 will require using Idaho allocated
renewable energy unless new clean energy resources are added. On an annual average
basis, with the new resource additions described in this plan, in 2030 and thereafter,
Avista's Washington customers will have net clean energy exceeding 100% of its retail
load. As discussed in the 2025 IRP, the amount of clean energy generated within a year
will exceed clean energy targets for the following reasons:
• Early acquisition of renewable energy to take advantage of lower cost,
lower complexity transmission interconnection projects, and the
Inflation Reduction Act (IRA) tax credits to lower customer costs
compared to building later. Early acquisitions will offset future load
growth and later higher renewable energy targets.
• The "use" rules of clean energy are subject to final WUTC
determination. It is possible any renewable energy generation
exceeding load within a defined period, such as a month or a period
of the day and may not qualify as clean energy and therefore requiring
additional renewable energy to ensure generation in other periods
either for compliance of planning.
• Planning for the 100% clean energy goal in 2045 requires additional
clean energy resources for contingency planning in the event of low
renewable energy production years and to meet 100% of load rather
than "retail" load, where load includes line losses.
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Table 2: Clean Energy Load and Resource Balance (aMW)
Retail Sales 704.9 708.1 709.3 708.4 708.7 709.8 711.9 718.8 727.5 737.1
PURPA 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9 20.9
Solar Select 5.7 5.7 5.6 5.5 5.5 - - - - -
Net Requirement 678.2 681.5 682.9 681.9 682.3 688.8 691.1 697.9 706.5 716.2
Target Clean%for Primary Compliance 66.0% 69.5% 73.0% 76.5% 80.0% 80.0% 80.0% 80.0% 85.0% 85.0%
Clean Energy Goal 447.6 473.6 498.5 521.6 545.8 551.1 552.9 558.3 600.6 608.8
Washington Allocated Share
Clark Fork&Spokane River Hydro 297.1 288.5 289.3 296.8 299.2 304.1 305.6 308.6 310.9 312.8
Mid-Columiba and CBH Hydro 159.9 167.2 165.4 165.0 162.2 163.2 164.5 165.6 130.8 131.0
Kettle Falls 23.3 21.1 18.7 17.7 17.8 18.8 17.8 17.51 16.8 16.3
Wind PPAs 86.6 87.0 87.0 87.3 87.3 87.4 87.3 87.6 87.9 88.1
Solar PPA - - - - - 5.3 5.3 5.3 5.2 5.2
Available Resources 566.9 563.9 560.4 566.8 566.5 578.8 580.5 584.7 551.5 553.4
Position Before Idaho Transfers 119.3 90.2 61.9 45.2 20.7 27.71 27.6 26.3 (49.0) (55.4)
Idaho Transfers (Wind, Biomass, Hydro PPA) 118.6 121.3 119.0 119.0 119.1 142.4 142.2 142.6 142.1 141.7
Position After Available Idaho Transfers 237.9 211.5 180.9 164.2 139.8 170.1 169.8 168.9 93.1 86.3
Proposed Wind Additions - - - 75.9 152.0 221.6 253.2 288.2 288.6 289.4
Proposed Solar Additions 0.1 0.2 0.3 0.4 0.5 0.7 0.8 0.9 1.0
Total Proposed Clean Energy Additions 0.1 0.2 76.2 152.5 222.1 253.9 289.0 289.5 290.4
Net Position w/Idaho Transfers 237.9 211.6 181.1 240.3 292.2 392.3 423.7 458.0 382.6 376.7
Net Position w/o Idaho Transfers 119.3 90.3 62.1 121.3 173.1 249.91 281.51 315.41 240.5 235.0
WA Allocated Resources as % Retail Load 84% 83% 82%1 94%1 105% 116% 121%1 125%1 119% 118%
Clean Energy Action Plan Requirements
CETA commits Washington to greenhouse gas emission free electricity supply by 2045.
RCW 19.280.030 provides requirements for a CEAP and WAC 480-100-620 expanded
these requirements for Investor-Owned Utilities. Avista's CEAP meets the following
requirements:
A. Be at the lowest reasonable cost;
B. Identify and be informed by the utility's ten-year cost-effective conservation
potential assessment as determined under RCW 19.285.040-1
C. Identify how the utility will meet the requirements in WAC 480-100-610 (4)(c)
including, but not limited to:
• Describing the specific actions the utility will take to equitably distribute
benefits and reduce burdens for highly impacted communities and
vulnerable populations;
• Estimating the degree to which such benefits will be equitably distributed
and burdens reduced over the CEAP's ten-year horizon; and
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Washington Clean Energy Action Plan
• Describing how the specific actions are consistent with the long-term
strategy described in WAC 480-100-620 (11)(g).
D. Establish a resource adequacy requirement;
E. Identify the potential cost-effective demand response and load management
programs that may be acquired;
F. Identify renewable resources, non-emitting electric generation, and distributed
energy resources that may be acquired and evaluate how each identified
resource may reasonably be expected to contribute to meeting the utility's
resource adequacy requirement;
G. Identify any need to develop new, or to expand or upgrade existing, bulk
transmission and distribution facilities;
H. Identify the nature and possible extent to which the utility may need to rely on an
alternative compliance option identified under RCW 19.405.040 (1)(b), if
appropriate; and
a. Incorporate the social cost of greenhouse gas emissions as a cost adder
as specified in RCW 19.280.030(3).
A. Lowest Reasonable Cost
The CEAP is a derivative of the 2025 Electric IRP. The IRP selects the lowest cost
resource portfolio given policy constraints, such as available resource types and lower
emissions requirements for new resources. A Mixed Integer Program (MIP) optimizes
resource options to choose the lowest cost portfolio given resource needs and available
options. The model simultaneously selects both supply- and demand-side resources to
reach a solution. It also considers transmission costs, availability of resources, and all
identified non-energy impacts to evaluate the social cost of different resource choices.
Chapter 2 of the 2025 IRP describes the Preferred Resource Strategy (PRS) over the
next 20 years and covers the needs for Avista's customers. This CEAP identifies the
expected resources for the 2026-2035 period meeting only Washington's policy
requirements and needs. Avista currently does not allocate supply-side resources by
state. New resources identified in this plan will be allocated to Washington using Avista's
Production Transmission (PT) ratio unless a new allocation methodology is developed
and approved by each state commission.
B. Energy Efficiency
Avista contracted with Applied Energy Group (AEG) to conduct an independent
conservation potential assessment (CPA) of Avista's service area. A summary of the
study is in the 2025 IRP's Chapter 6 and AEG's report is available in Appendix C. AEG
identified 1,486 programs for both Avista and the Northwest Energy Efficiency Alliance
(NEEA) to implement (if cost effective). If all these programs were successfully
implemented and customers agreed to fully participate, energy sales would reduce by
903 GWh (103 aMW) through 2035. Not all potential program measures are economic for
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Washington Clean Energy Action Plan
Avista's customers. To identify the cost-effective measures for implement, the IRP
capacity expansion model conducts a Total Resource Cost (TRC) test of each energy
efficiency measure compared to other resource alternatives. The analysis found 368.4
GWh (42.1 aMW) to be cost effective on a cumulative basis if customers participate as
forecasted. In addition to the energy savings, peak loads winter peak load is reduced by
85 MW in December and 71 MW lower in the August peak by the end of 2035. Figure 1
shows the annual cost-effective energy efficiency expected for each customer group.
Avista's 2026-2027 target is 73,672 MWh
Figure 1: 10-Year Cost Effective Conservation Potential Assessment
400
368
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2026 2027 2028 2029 2030 2031 2032 2033 2034 2035
C. Equity and Customer Benefits
Equity and incorporating the tenets and principles of Energy Justice, including
recognition, procedural, distributive and restorative, are crucial in the transition to clean
energy and form the core of the CEAP.105 The CETA guidelines not only focus on the
advantages of energy usage, but also on the benefits and opportunities it brings, including
economic growth, social health and safety improvements, and the reduction of GHG
emissions benefiting the environment. There is an emphasis on how these benefits are
distributed among communities. Utilities are required by CETA to address these topics
when planning to acquire resources to minimize unequal access to benefits or
disproportionate burden of risks — allowing all customers to share in the benefit and
105 The Company defines equity as fair and just inclusion,treating all customers fairly, recognizing that each
person has a unique circumstance, and allocating resources and opportunities in a manner which achieves
an equal outcome.
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Washington Clean Energy Action Plan
burden. Specifically, CETA requires all customers to benefit from the transition to clean
energy:
"through (i)the equitable distribution of energy and nonenergy benefits
and reduction of burdens to vulnerable populations and highly
impacted communities, (ii) long-term and short-term public health and
environmental benefits and reduction of costs and risks; and (iii)
energy security and resiliency."'06
CETA also has a strong public participation focus to ensure customers and communities
can provide input on clean energy decisions. While not specifically defined as "energy
justice tenets,"the nature of CETA requirements align with the definition of energy justice,
which is as follows:
"Energy justice refers to the goal of achieving equity in both the social
and economic participation in the energy system, while also remediating
social, economic and health burdens on marginalized communities.
Energy justice explicitly centers the concerns of frontline communities
and aims to make energy more accessible, affordable, clean and
demographically managed for all communities.11107
These requirements create a broader consideration of benefit types, increase input of
interested parties regarding equity issues, and promote continuous progress for resource
evaluations and the overall delivery of the energy system within the traditional planning
process. To ensure Avista is effectively planning for equitable outcomes, the four tenets
of energy justice — recognition, procedural, distributive, and restorative — are included in
the development of the CEAP and selection of resources.
Recognition Justice
Recognition justice primarily focuses on whose energy service has been, or is currently,
impacted in a disproportional manner. It is primarily concerned with the historical context
and seeks to understand how previous actions or policies have resulted in disproportional
outcomes. This "... requires an understanding of historic and ongoing inequalities and
prescribes efforts that seek to reconcile these inequalities."108
A key aspect of CETA includes a focus on Named Communities. These communities are
either socially or economically disadvantaged or sensitive to environmental impacts on
their health. Avista incorporated recognition justice into the IRP and CEAP through its
106 RCW 19.405.060(1)(c)(iii).
107 Shalanda Baker, Subin DeVar, and Shiva Prakash, "The Energy Justice Workbook" (Boston, MA:
Initiative for Energy Justice, December 2019),
https://ieiusa.org/wp-content/uploads/2019/12/The-Energy-Justice-Workbook-2019-web.pdf.
106 Final Order No. 09 in UG-210755, paragraph 56.
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work on the Named Community mapping tool. These maps overlay the Washington State
Department of Health (DOH) Environmental Disparities map of Avista's Washington
service territory. In addition, the White House's Justice 40 Initiative map, identifying
community burdens in the areas of climate change, energy, health, housing, legacy
pollution, transportation, water and wastewater, and workforce development, was
incorporated. These maps provide insight for identification of communities who may have,
or continue to, receive a disproportionate benefit or burden. This is more fully described
in the "Named Community Identification" section below.
Beyond a contextual understanding of disparities, recognition justice also validates lived
experiences, encourages constructive dialogue regarding methods for addressing
inequities, and ensures new policies do not exacerbate existing situations or create
unintended consequences. The Equity Advisory Group (EAG) was established in 2021 to
support these efforts. The EAG members have been instrumental in validating inequalities
in known Named Community areas and identifying additional communities or individuals
who have or are experiencing disparities within Avista's Washington service territory.
Through conversations with the EAG, public outreach and engagement efforts, Avista
began incorporating recognition equity into its planning efforts.
Procedural Justice
Procedural justice focuses on impartial, accessible, and inclusive decision-making.
Incorporating procedural justice into the IRP and CEAP process involves ensuring all
interested parties, especially those from Named Communities, have meaningful
opportunities to provide input to the decisions impacting them.
Throughout the IRP and CEAP's development, Avista promoted procedural equity in a
variety of ways:
• Engaged several advisory groups and encouraged participation in the
areas of equity, energy efficiency/demand response, energy
assistance, resource planning and the IRP's TAC, and Distribution
Planning Advisory Group (DPAG).
• Modified the TAC meeting's frequency and duration based on
feedback from participant's feedback.
• Reviewed and modified presentations to ensure more use of common
language (non-technical) where possible.
• Recorded presentations for ease of access at later dates/times.
• Posted IRP calculation workpapers to provide transparency.
• Posted presentations several days before meetings to provide more
time to develop questions and share concerns.
• Developed CBIs informing resource selection in consultation with the
EAG and reviewed publicly with the TAC.
• Ensured participation from customer advocates to represent
customers who may not be able to attend.
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• Evaluated baseline CBIs in relation to resource planning to track
progress, recognize, and acknowledge there are disparities and to
support transparency in Avista's actions and impacts.
• Enabled language translation and closed captioning on the Zoom
platform for public participation meetings.
• Posted input received from public meetings to support transparency
of feedback.
Avista's Public Participation Plan (PPP)109 informed tactics and strategies to facilitate
meaningful engagement. The PPP supports broad representation from interested parties
and customer advocates, providing additional opportunities for identifying and
considering policies or procedures going forward.
Distribution Justice
Distribution equity in the IRP and CEAP pertains to the allocation of advantages and
disadvantages of interim clean energy goals and targets and ensures they are allocated
between different communities or across generations. It not only focuses on the actions
taken but also on the communities affected, considering variations among them, such as
between Named Communities and the general customer base.
The foundation of energy equity emphasizes identifying benefits going beyond traditional
energy-related benefits. In IRP modeling, resource selection is based on either a
constraint (forcing an action) or a financial driver (cost or benefit) to incentivize resource
selection. Recent IRP's resource selection used additional modeling of non-financial
benefits, or Non-Energy Impacts (NEls), to highlight the interconnectedness of economic,
social, and environmental issues from resource selection.
To measure the distributional impacts of resource selection, CBI metrics are monitored.
The CBIs are designed to provide a transparent, consistent, and measurable way to track
progress and ensure accountability in equity areas including affordability, accessibility,
reliability, and environmental impacts. The inclusion of CBIs in resource modeling may
not fully inform economic resource selection, as the cost may exceed the financial
benefits, or may negatively impact a CBI metric. For example, affordability may be
negatively impacted if there is an increase in distributed energy resources (DERs). Avista
included an IRP scenario to maximize all CBIs regardless of the cost to the system. This
Maximum Customer Benefit scenario is described in Chapter 10 of the IRP. A forecast of
CBI changes relevant to this plan and the full 20-year IRP are discussed later in this
document.
Avista's approach to distributional justice and energy equity is comprehensive and
multifaceted. By focusing on CBIs and NEls, and addressing affordability, accessibility,
109 See Docket No. UE-210295 for Avista's 2021 Public Participation Plan and Docket UE-210628 for its
2023 Public Participation Plan.
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reliability, and environmental sustainability, Avista aims to ensure the transition to clean
energy is just, inclusive, and beneficial for all customers. See information below for more
about CBIs and their associated metrics.
Restorative Justice
Restorative justice focuses on systematic approaches to prevent harm from occurring or
continuing in the future. Striving to minimize disparities between Named Communities
and all customers, particularly in relation to areas of affordability, availability, and
accessibility, amongst others. Avista incorporates restorative equity in the following ways:
• Climate change impacts: The CEAP includes consideration for future weather
impacts in the load and hydro forecast. Avista also accounts for the Social Cost of
Greenhouse Gas (SCGHG) in resource decisions as directed by CETA.
• Energy Efficiency efforts: Energy efficiency provides significant value in support
of clean energy goals and as a method for restorative equity. By supporting more
energy efficiency in Named Communities, Avista provides opportunities to mitigate
disparities. As previously mentioned, "fairness" is the act of being fair, impartial,
and just. Through these additional energy efficiency efforts, Avista is essentially
meeting customers where they are — seeking to "close the gap" in disparities.
• Named Community Investment Fund (NCIF): Avista created the NCIF to fund
projects for customers in Highly Impacted Communities or from Vulnerable
Populations, jointly referred to as Named Communities. This approximately $5
million annual fund enables energy and non-energy projects for these communities
where they may not be able to complete or fund on their own. Avista accounts for
these energy impacts in the CEAP by including an additional $2 million of annual
energy efficiency spending for Named Communities in the energy efficiency target.
Further, it includes an additional spending requirement for local DERs as a
placeholder for future NCIF selected projects. These investments in Named
Communities will influence local economic development and provide specific
opportunities for people in these communities.
Achieving equity in Washington's clean energy transformation is not limited to IRP/CEAP
planning. A broader, Company-focused effort is being made to ensure an equitable
transition — one that is fair, impartial, and provides opportunities for all customers
regardless of their unique circumstance. Avista has several efforts in progress to help
incorporate equity throughout Avista's operations. These efforts include an equity focus
on capital planning, energy efficiency and weatherization, affordability, and distribution
planning.
Challenges to Implement Energy Equity Tenets
While Avista has taken several steps to incorporate energy equity tenets throughout its
resource planning efforts, challenges remain regarding these efforts. The Company
briefly discusses these challenges below and will provide additional details pertaining to
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specific actions to overcome these challenges and identified inequities in its Clean Energy
Implementation Plan (CEIP). Incorporating equity tenants and implementing strategies to
address inequities is not a one-and-done activity but is an iterative improvement process
as Avista continues to engage with the communities it serves. Avista will consider the
equity impacts of business decisions, and where feasible or practical to benefit all
customers, implement equity-related improvements. Operational izing equity and energy
justice principles — moving from theory to practice — has inherent challenges including,
but not limited to, the following:
Data availability and quality
Obtaining accurate data on energy usage, demographics, and socio-economic factors is
crucial. In many areas, such data may be incomplete, outdated or only available through
a third-party, making it difficult to identify and address disparities.
Specific Action: To improve data availability and quality, where possible, Avista
contracts with a third-party data provider for personal identifiable information such
as income, if they rent or own a home, age, marital status, etc., and match that
data with internally available customer data. To enhance data integrity and
accuracy, Avista has improved data collection and validation efforts for CB1
reporting and other metric obligations through a centralized data analytics team.
Further, the Company recognizes there is a need for accurate, complete data
which is consistent across all business units.
Engaging interested parties
Effective outcomes require collaboration among all interested parties, beyond those who
have historically participated in how Avista generates and delivers energy now and into
the future. Directly engaging customers or advocates on their behalf is often difficult due
to several factors, including having a desire to participate, or the ability to participate
based on existing priorities and resource constraints within external organizations.
Specific Action: To mitigate public awareness barriers, Avista hosts quarterly
public participation meetings, provides social media campaigns to increase public
meeting awareness, attends and participates in community engagement events,
and contracts with a third-party to deploy customer engagement strategies and
improve outreach effectiveness. Additionally, Avista is developing videos to
support its clean energy initiatives to broaden awareness and increase customer
participation. The Company continues to include its EAG in conversations
regarding methods for contacting "hard to reach" customers and those in Named
Communities. Although the Company has an obligation to promote awareness and
conduct engagement efforts in good faith, a decision to participate in the activities
must come from the customer or the advocacy groups. Avista's 2025 Public
Participation Plan, due by May 1, 2025, will outline specific actions to overcome
barriers to customer engagement and participation.
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Funding and Resources
Implementing equity-focused initiatives often requires significant investment. Limited
funding can hinder the development, operation and awareness of programs supporting
Named Communities.
Specific Action: In the Company's 2022-2025 CEIP, Avista implemented its
Named Community Investment Fund (NCIF), spending up to $5 million annually
for direct investments in Named Communities, including investments in resiliency
and additional energy efficiency. In addition, Avista has expanded its Low-Income
Rate Assistant Program (LIRAP) to include a tiered bill discount program, known
as My Energy Discount, an Arrearage Forgiveness Program, and an Arrearage
Management Program, all with the intention of reducing energy burden and making
energy service more affordable. Avista is actively working on ways to increase
participation in these energy assistance programs and on continued investments
in Named Communities.
Technical Expertise
Customers may want to participate to a greater extent in resource planning Technical
Advisory Committee (TAC) meetings; however, due to the technical nature of long-term
system planning and inherent complexities, do not feel they have the skillset to do so.
Specific Action: Avista recognizes the IRP TAC process is highly technical in
nature with complex terminology and lengthy meeting times. To reduce meeting
fatigue, the Company pivoted from half day meetings once a month, to shorter
meetings every two to three weeks during the planning phase. Additionally, various
components of the Company's IRP are discussed throughout the CEIP public
participation meetings where the language and discussion topics are shared using
customer friendly terminology, instead of technical verbiage that is used during the
TAC meeting process. Overcoming technical barriers is broader than a single
Company's specific action and will take a collaborative approach between utilities,
the Commission and its Staff, customer advocate groups, and other interested
parties.
Named Community Identification
Avista identified communities who are disproportionally impacted by adverse
socioeconomic conditions, pollution, and climate change, among others, to ensure
planning and implementation processes are fair and to equitably distribute clean energy
transition benefits. Avista identified two types of community groups, Highly Impacted
Communities and Vulnerable Populations (WAC 480-100-605), or collectively Named
Communities, defined as follows:
• Highly Impacted Community is designated by the Washington Department of
Health (DOH) based on cumulative impact analyses in section 24 of this act or a
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community located in census tracts that are fully or partially on "Indian country" as
defined in 18 U.S.C. Sec. 1151.12.
• Vulnerable Populations are communities experiencing more risk from
environmental burdens due to:
o Adverse socioeconomic factors, including unemployment, high housing and
transportation costs relative to income, access to food and health care, and
linguistic isolation; and
o Health sensitivity factors, such as low birth weight and higher rates of
hospitalization.
Avista relies on information provided by the Washington State Health Disparities Map
from the DOH to identify Highly Impacted Communities. For each census tract in the state,
the DOH developed a score to measure disparities ranked between 1 and 10 for
Environmental Exposure, Environmental Effects, Socioeconomic Factors, and Sensitive
Populations. Communities where the combined average score of the four categories was
nine or higher are considered Highly Impacted Communities. The DOH also includes any
areas fully or partially within "Indian Country".110
In Avista's 2021 CEIP, its methodology to determine Vulnerable Population
characteristics was conditionally approved.1 ' The EAG and other advisory groups helped
Avista determine the geographic boundaries of Vulnerable Populations for the 2021 CEIP
by using the Health Disparities Map112 community rating system for Socioeconomic
Factors and Sensitive Population. The maps identify areas on a scale of 1 to 10, where
10 is an area with the most significant health disparity. Avista focused on identifying
census tracts not otherwise identified as a Highly Impacted Community whose
socioeconomic factor or sensitive population score was 9 or 10. This methodology was
conditionally approved contingent upon the incorporation of additional metrics as
identified by Avista and the EAG. The criteria for determination of Vulnerable Populations
(as developed by DOH) was reviewed to ensure these socioeconomic or sensitivity
factors applied specifically to Avista's customers. Beyond inclusion of those indicators,
additional collaboration with its EAG members resulted in a review of other traits that
could be considered in the final determination of Avista's Vulnerable Populations. Avista
also overlayed the Justice40 map of disadvantaged communities on its Named
Community map to provide additional insights into challenges within its service territory.
The Justice40 map provides a more in-depth look at indicators that are directly impacted
by the energy industry. In combination, these maps provide an opportunity to further
improve recognition justice, as well as monitoring, tracking and allocating resources to
help ensure equity through energy transformation.
10 The DOH's list of Highly Impacted Communities originally included areas misidentified as "Indian"
country due to GIS borderline errors. Avista excluded these census tracts from its list for this report.
111 Docket No. UE-210628.
112 https://fortress.wa.gov/doh/wtnibl/WTNIBL/Map/EHD
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The maps of both types of Named Communities are shown in Figures 2 through 4 below.
Avista is working with the EAG to determine other ways to identify Vulnerable
Populations.
Figure 2: Washington Service Area Named Communities
Legend
i
1
5
y y'
i
20 40 ,"Milrs
I i
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Washington Clean Energy Action Plan
D. Resource Adequacy
Avista must maintain enough resources to reliability serve current and future customers.
Planning an electric system using a geographic footprint greater than a single utility take
may take advantage of load and resource diversity of load and resources of other utilities.
To address this, Avista is participating in the development of Western Power Pool's
Western Resource Adequacy Program (WRAP)113 Participation in regional resource
adequacy efforts is important because Avista can benefit from the diversity and availability
of other utilities resources, resulting in deferring the need for new resources. Until the
WRAP is operational and binding, Avista continues to use its own planning standard of
ensuring a 5% Loss of Load Probability (LOLP) including the ability to access 330 MW of
market power. This LOLP planning standard results in a 24% planning margin added to
the 1-in-2 peak load forecast, positioning Avista to withstand energy uncertainties. For
summer planning, Avista uses the size of its single largest contingency resource (Coyote
Springs 2) to determine the summer planning reserve margin, this results in a metric of
16%.
The 2025 IRP included an analysis of Avista's resource position in 2030 and finds with
the current resources and projected retirements to cover both Washington and Idaho
load, the system will not meet the resource adequacy requirement. With the resources
identified in this CEAP for Washington, combined with additional resources needed for
Idaho customers, the system would be resource adequate. These additional resources
include a 90 MW natural gas-fired Combustion Turbine (CT), energy efficiency, and DR
programs. With these additions, the system is resource adequate in 96.8% of future
weather conditions (above the 95% threshold) assuming 330 MW of market reliance. In
3.2% of future scenarios where resource adequacy is not met, Avista would be dependent
on the energy market or load curtailment beyond the 330 MW threshold. While the CEAP
is directed at resource decisions for Washington, the resources needed for Idaho directly
affect Washington due to the unique position where resources are allocated to each state
using the production transmission (PT) ratio as opposed to which state's need drives the
resource as modeled in the IRP. When Avista acquires resources, regardless of the
primary driver, both states share the benefits and the costs using a pre-approved
allocation methodology through the PT ratio. Avista will need to issue a Request for
Proposal (RFP) of at least 90 MW of winter capacity with on-line delivery by the winter of
2029/2030 to maintain a reliable system. The new capacity addresses load growth,
expiration of a long-term PPA, and the potential retirement of the Northeast CT. However,
based on the circumstances of these factors this resource need could change.
13 The WRAP is currently operated by the Southwest Power Pool (SPP) on the behalf of WPP.
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E. Demand Response & Load Management Programs
Avista and a large industrial customer agreed to a 30 MW DR program after the 2021
IRP. Following the 2021 CEIP, Avista began multiple DR pilots including an electric Time
of Use (TOU) rate for residential and commercial customers, a Peak Time Rebate (PTR)
for residential customers, and a partnership with NEEA to test grid-enabled CTA-2045
water heaters.114 The 2025 IRP includes a biennial assessment of the DR potential
programs within Avista's service area conducted by a third-party-Applied Energy Group
(AEG). The potential assessment identified 101 MW of potential winter peak savings
could be realized by 2035 if all programs were started by 2026. However, similar to the
energy efficiency potential, not all programs are cost effective. Further, DR programs
should only be implemented when the utility has a capacity need. In some cases,
programs are cost effective within the plan, but not within every year of the 20-year study.
Overall, nine programs within the 20-year plan are selected, but only four programs within
the first 10-years of the plan. A summary of these programs and their expected peak
savings is shown in Table 3. As behavioral DR programs are designed to affect energy
usage behavior during peak usage events, it is nearly impossible to measure total
program savings and the amount of customer load changes.
aum %.,amulative Demand Response (MW)
RebateBattery EV Time Variable Peak Time Total
Energy of Use Peak
Storage . .
2026 0.03 0.09 0.35 - 0.47
2027 0.10 0.30 1.00 - 1.40
2028 0.24 0.54 2.19 - 2.97
2029 0.92 0.80 3.17 - 4.89
2030 2.47 1.06 3.70 - 7.23
2031 3.44 1.35 3.88 - 8.67
2032 3.83 1.68 3.92 - 9.43
2033 4.28 2.02 3.92 - 10.22
2034 4.75 2.41 3.93 - 11.09
2035 5.39 2.85 3.95 0.20 12.38
114 According to the Customer Technology Association (CTA), the CTA-2045 standard is a modular
communications interface to facilitate two-way communications with residential devices for energy
management.
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F. Clean Energy Acquisitions
The 2025 IRP identifies multiple clean energy additions including community solar and
utility scale wind. Currently, Avista is not proposing non-emitting electric generation
(energy storage) unless capacity needs change due to unexpected load growth or
generation capability/availability changes. The selected resources within the PRS will
contribute to meeting the clean energy standards of CETA and provide minimal resource
adequacy capacity to the system. While the assigned Qualifying Capacity Credits (QCCs)
are relatively small for meeting peak load, one exception is Montana wind. Although, if
there is a future downward QCC revision based upon recent cold weather performance,
Avista may need a traditional capacity resource.
Avista's system capacity need by 2035 is estimated to be 225 MW for winter peak and
155 MW for summer peak, while the capacity need for its Washington portion of the
portfolio is estimated to be 107 MW for winter peak and 93 MW for summer peak (prior
to the DR selections covered earlier in this plan). As discussed earlier, Avista currently
does not have an allocation methodology outside of the PT ratio for cost recovery of
assets using a fixed ratio. This results in the 2025 IRP assuming a greater resource need
for Idaho over Washington due to less PURPA generation and DR within the Idaho
jurisdiction, even though Washington load is larger. Until an agreement is reached
regarding resource allocation, the new resources resolving these deficits will continue to
be split using the existing cost recovery methodology rather than the IRP methodology.
Community Sola
Avista's 2025 IRP includes a placeholder for community solar ranging from 0.5 MW to 1
MW annually. The forecasted first addition begins in 2027 utilizing grants from the
Department of Commerce and Avista's NCIF. Within the CEAP time horizon, a total of 5.9
MW of distributed solar could be installed, contributing 0.2 MW to winter and up to 1.8
MW toward summer resource adequacy. Depending on location, grant availability and
need, energy storage could also be added to the final resource configuration. To ensure
the best locations and needs are met, this CEAP is not prescriptive about how solar will
be added to the system but will seek the best use of available grant funds in achieving
energy burden reductions. Avista will continue its community solar development efforts
and may provide a proposal in its 2025 CEIP.
Wind
Over the 10-year CEAP period, as seen in Table 4, 736 MW (257 aMW) of wind is
selected for Washington in the 2025 IRP. Including Idaho, total system wind additions are
857 MW. Wind resources selected by the planning model includes wind within Avista's
service area, on Montana and other transmission systems. Procuring wind early in the
planning horizon makes this resource more economic due to low wind PPA pricing
forecasts, the availability of tax incentives from the Inflation Reduction Act (IRA), and high
forecasted wholesale electric prices allowing the use of surplus energy sales to reduce
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customer costs. However, if the tax credits were not available, wind selection would occur
later in the planning horizon, closer to the energy needs of the system.
The actual amount of wind over the CEAP period is subject to multiple risks and may be
reduced and/or delayed as a result of transmission access or changes in energy markets.
While Avista's service area has significant wind potential, the ability to interconnect and
deliver the wind to customers is limited without major transmission investments. If other
utilities or developers export projects from Avista's transmission balancing area, Avista's
ability to acquire low-cost wind projects for its customers will be limited until new
transmission can be built.
Table 4: Wind Selections (MW)
WashingtonYear
Allocated Allocated
Wind Wind
(WA share)
2026 - -
2027 - -
2028 - -
2029 200 -
2030 200 -
2031 100 66
2032 - 66
2033 - 104
2034 - -
2035 - -
Total 500 236
As mentioned earlier, Avista is not proposing any GHG-emitting resources or energy
storage to directly serve Washington due to the wind, DR, and energy efficiency additions
contributing to the additional resource adequacy needed to meet load growth.115 For the
wind additions, the total QCC is small compared to the total wind capacity, but it does
satisfy most of the resource need meeting 63 MW toward the winter and 74-83 MW toward
the summer resource adequacy metrics. However, wind does have a significant risk of
not performing in severe cold and excessive heat. Regardless of contribution to capacity
needs, relying on wind for resource adequacy creates risk to customers. As regional
resource adequacy planning matures through the WRAP process in the WECC, energy
storage may enter the resource need assessment to account for any lost capacity formally
attributed to wind energy.
15 Avista does not model jurisdiction reliability metrics due to the system functions as one. It is possible
without the 90 MW CT allocated to Idaho, the Washington portion of resources is not adequate if only
Washington load and resources were available.
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Resource Acquisition
The wind acquisitions discussed in this plan will be managed through a request for
proposal (RFP) process. An all-source RFP is likely to be issued in 2025 to evaluate all
resource options to meet specific energy and capacity requirements. Through this
process, Avista may find an alternative to wind energy such as acquiring more regional
hydroelectric generation, a combination of solar and energy storage, or a different wind
source than included in this plan. Furthermore, the RFP may show the cost of new wind
generation is not economic due to higher net customer costs, resulting in delayed
acquisition.
The RFP process will also be combined with meeting system needs (i.e., Idaho) where
other capacity resources such as natural gas, energy storage, or DR aggregation could
be considered for meeting either the Washington or Idaho portion of system load. Based
on information in this plan, and subject to changes due to load and resource availability,
the all-source RFP will seek 116 MW of winter capacity by November 2029 and 125
aMW116 of renewable energy as early as 2029. Avista's RFP release will provide specific
requirements subject to updated information once this IRP process is finalized.
G. Transmission & Distribution
Avista is planning significant changes to its transmission system over the next 10 plus
years to enable access to energy markets and to integrate new resources. Large
transmission development exceeds the planning horizon of this CEAP and often changes
over time. The transmission projects under consideration are included in this plan, but not
all are committed.
10-Year System Planning
Avista's system planning team develops a detailed 10-year System Plan and System
Assessment with updates every two years. The System Assessment covering local
planning, was released in November 2023, followed by the System Plan in February
2024. Both plans are in Appendix D.
The 10-year System Plan shows Avista's strategy to develop system reinforcements
required to meet transmission system needs for load growth, adequate transfer capability,
requests for generation interconnections, line and load interconnections, and long-term
firm transmission service. The two-year System Assessment provides technical analysis
demonstrating system performance and describes conceptual solutions to mitigate
operational issues to maintain expected performance.
16 Renewable generation is preferred between July and March as the other months typically have excess
renewable energy from hydroelectric production.
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Blue Bird — Garden Springs 230 kV Project
Avista's system planning through the 10-year assessment identified transmission system
needs for load growth across the south and west of Spokane. Studies show system
operability is strained and results in reduced system flexibility, affecting safety, system
resiliency, and ultimately service to customers. Continued load growth will amplify this
situation.
The Blue Bird - Garden Springs 230 kV project was identified as the backbone segment
of a broader West Plains Transmission Reinforcement project. The project's primary goal
is to develop a new and independent 230 kV source west of Spokane. This goal will be
addressed by sourcing 230 kV from BPA Bell - Coulee #5 230 kV Transmission Line to
improve contingency performance and to increase system stability. The new 230 kV
source will provide the required reliability and operational flexibility needed to serve
current and forecasted loads.
An additional benefit of developing a new and independent 230 kV source west of
Spokane is the increased transmission service capability this project is expected to bring.
The location of this new 230 kV connection is anticipated to increase power transfer
capability between Avista and BPA by 10-30% depending on the season.
North Plains Connector
The 2025 IRP evaluated a proposed regional transmission project to connect the Western
and Eastern Interconnects. The project is developing a 3,000 MW capacity DC line
between Colstrip, Montana and North Dakota with an on-line date of 2033. The end points
in North Dakota would give Avista access to both the Midcontinent Independent System
Operator (MISO) and Southwest Power Pool (SPP) markets to buy or sell power and
provide access to generation resources in the mid-continent with different weather
patterns. Avista studied this project in the IRP as a capacity only resource for resource
adequacy to validate if the project cost could be justified based on this portion of the
benefit."' An additional significant benefit is energy arbitrage by taking advantage of
higher or lower prices in other markets and the Mid-Columbia market. These arbitrage
benefits were not evaluated in the IRP as the analysis was still being conducted during
the development phase. The capacity benefits from market access indicates participating
in at least 300 MW of capacity from the North Plains Connector is beneficial to customers
and was included in the 2025 IRP. If this project can be completed by 2033, it could
replace capacity resources identified in the 2025 IRP's portfolio scenario analysis. Avista
has not committed to this project but is actively following its progress and studying
potential participation.
"'The IRP analysis was conducted prior to the announcement by the DOE to allocate a $700 million Grid
Resilience and Innovation Partnership (GRIP) grant to the project.
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Colstrip Transmission System Upgrade
Avista and the other owners of the Colstrip Transmission System are evaluating upgrades
to the existing 500 kV transmission lines and supporting its 230 kV and 115 kV
infrastructure. These upgrades would increase power transfers out of Montana by
approximately 900 MW. The purpose of this study is to better identify the simultaneous
increases in transfer capability across the Montana to the Northwest and West of Hatwai
WECC rated paths. Montana to Washington 500 kV transmission system upgrades were
last studied by NorthWestern, BPA, and Avista in May 2012, as part of the Colstrip to Mid-
Columbia Upgrade Project Study.
Lolo-Oxbow Upgrade and Optimizatior
Avista, as a prime recipient, in partnership with Idaho Power Company, is seeking grant
funding for the Lolo - Oxbow Transmission Upgrade and Optimization project. This project
will upgrade the Lolo - Oxbow 230 kV Transmission Line with high-capacity conductors,
as well as wildfire resilient designs and materials. Additionally, the project includes
integrating Idaho Power's new Pallette Junction Station and two SmartValve technology
deployments. These improvements will increase interregional transfer capability by 450
MW between the Pacific Northwest and Mountain regions, presenting an opportunity to
increase the build of renewable energy resources in the region.
The Lolo - Oxbow Upgrade and Optimization project would bring innovative technologies
together resulting in improvements to interregional transfer capability by 450 MW from
Avista to Idaho and up to 185 MW in the opposite direction. The two innovative
technologies planned for this project are:
3) SmartValve technology that opens the door to dynamically controlling and
optimizing power flows, and
4) Infravision technology that speeds transmission line construction with drone pull-
line stringing instead of helicopter use.
The local communities and region would benefit from capacity upgrades enabling future
generation interconnection opportunities to the Lolo - Oxbow 230 kV Transmission Line.
If awarded, there will be community benefit funding available for up to $3.3 million.
Additionally, through these upgrades, Avista will work towards further workforce
development in energy-supportive roles, such as on-site equipment training, special
operator training, and other job skill opportunities.
New Resource Interconnectior
New resources may require an interconnect and additional reinforcements elsewhere in
the system. When evaluating generic resources in the IRP, estimated costs are assigned
to these resources as a placeholder for potential upgrades, but until specific resources
are committed, the transmission upgrades are unknown. Further, the IRP identifies if
there is not enough local capacity within an area where it is likely new resources would
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be located. Avista identified upgrades in Rathdrum, Idaho as a necessary improvement if
additional generation capacity is chosen in northern Idaho. When Avista evaluates
projects within the RFP process, it ensures projects are progressing through the
transmission cluster study process to confirm the project is deliverable to the system
within necessary timelines. The cluster study process outlines the necessary system
upgrades, construction timing, and costs to integrate proposed resources and the studies
can be found on the Avista's transmission (OASIS) website.118
H. Alternative Compliance & Social Cost of Greenhouse Gas
Beginning in 2030, Avista's Washington electric retail sales must be greenhouse gas
neutral, this means up to 20% of Washington's retail load can be offset with alternative
compliance.119 There are four main types of alternative compliance:
1. Compliance payment
2. Unbundled Renewable Energy Credits (RECs)
3. Investing in transformation projects
4. Using energy from a municipal solid waste facility120
To make progress toward the 2045 target, Avista assumes the amount of alternative
compliance allowed will be lower each compliance period with 20% allowed for the 2030-
2033 period and 15% between 2034 and 2037. Avista plans to use unbundled RECs or
excess clean energy it controls to meet the 2030 neutral standard. Avista has access to
three types of unbundled RECs:
1. RECs from excess energy beyond what will count toward "primary" compliance
under the final clean energy "use" rules,
2. Renewable energy Avista owns and is allocated to Idaho customers, and
3. RECs purchased on the open market. (absent a federal or state law requiring
retirement of those RECs).
Avista will have significant RECs available from Idaho to sell to Washington customers at
market prices. Table 5 is an estimate of the amount of alternative compliance Avista could
utilize to meet the 2030 carbon neutral requirements.
118 (Open Access Same-Time Information System), https://www.oasis.oati.com/avat/index.html.
119 RCW 19.405.040 (1)(b).
120 Using electricity from an energy recovery facility using municipal solid waste as the principal fuel source,
where the facility was constructed prior to 1992, and the facility is operated in compliance with federal laws
and regulations and meets state air quality standards. An electric utility may only use electricity from such
an energy recovery facility if the department and the department of ecology determine that electricity
generation at the facility provides a net reduction in greenhouse gas emissions compared to any other
available waste management best practice. The determination must be based on a life-cycle analysis
comparing the energy recovery facility to other technologies available in the jurisdiction in which the facility
is located for the waste management best practices of waste reduction, recycling, composting, and
minimizing the use of a landfill.
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Table 5: Alternative Compliance
Lr Alternative Retail Maximum
Compliance
Percentage (aMW)ear
Compliance
2030 20% 682 136
2031 20% 689 138
2032 20% 691 138
2033 20% 698 140
2034 15% 707 106
2035 15% 716 107
Transformation projects could be used for alternative compliance if cost-effective
compared to unbundled RECs. To date, the transformation project requirements and
accounting of the benefits toward alternative compliance are unknown, but Avista expects
it may have some cost-effective options to use this mechanism from efforts in its
Transportation Electrification Plan.
The last alternative compliance option is energy from a municipal solid waste facility, but
this option has challenges. Avista currently purchases energy from a municipal solid
waste facility, and it may meet this qualification in the future, but the output from the
project is currently purchased as a PURPA resource through 2037. As a PURPA
resource, it is deducted from retail load so counting the facility as alternative compliance
would be double counting the resource.
sociai %,ost u, greenhouse Gas
Avista includes the Social Cost of Greenhouse Gas (SCGHG) within the portfolio model
when it optimizes resource selection. Each resource with GHG emissions is assessed the
cost as part of the portfolio optimization — see Figure 5 (green line) for pricing. The
Washington share of existing resources and the potential new resources serving
Washington are assessed this charge when optimizing the portfolio. The SCGHG is not
included in Washington's share of resource dispatch within the modeling framework, but
rather the cost of the Climate Commitment Act (CCA) emission allowances beginning in
2031. Due to uncertainty of how CCA allowance costs will be effectively "charged" to
customers, Avista does not include the CCA or SCGHG costs when forecasting future
rates shown in the 2025 IRP Chapter 2.
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Figure 5: Social Cost of Greenhouse Gas Prices
$250
—SCGHG(2007$) —SCGHG(2022$) —SCGHG Nominal$
$200
C
O
12 $150
V
•L
d
L.
$100
Q
$50
$0
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O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
Customer Benefit Indicator Analysis
This CEAP includes forecasts of the relevant CBI impacts for supply- and demand-side
resource selections from the 2025 IRP. The 2021 CEIP contained 14 CBIs, including 31
metrics for measuring the impact of those CBIs. Not all metrics are related to resource
planning, but 11 do relate. This section demonstrates how the metrics may change with
the 2025 IRP's resource strategy. Table 6 includes all metrics from the 2021 CEIP. Bolded
CBIs are forecasted in this plan since they are relevant to resource planning. These
metrics help measure the effects of the clean energy transition and broaden the focus on
equity among customers.
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Table 6: Customer Benefit Indicators
Customer Benefit
Equity Area Indicator tric
(1) Participation in — Participation in weatherization programs and energy
Company Programs assistance programs (all and Named Communities)
Residential rebates provided to customers residing in
Named Communities and rental units Condition #17
Saturation of energy assistance programs (all and
Named Communities
Affordability (2) Number of — Number and percent of households (all customers,
households with a known low-income customers and Named Communities)
High Energy Condition #18
Burden (>6%) — Average excess burden per household (all
customers, known low-income customers and Named
Communities
— Number of households with high energy burden by
Named Community subset(Condition#38)
(3) Availability of — Number of outreach contacts
Methods/Modes of — Number of marketing impressions
Outreach and — Increase in translation services
Communication
(4) Transportation — Number of trips provided by Community Based
Electrification Organizations
— Number of public charging stations located in Named
Communities
(5) Named Community — Total MWh of distributed energy resources 5 MW
Accessibility Clean Energy and under
— Total MWh of energy storage resources under 5 MW
and under
— Number of distributed renewable energy resources and
energy storage resources sites, projects, etc.,).
(6) Investments in — Incremental spending each year in Named Communities
Named — Number of customers/and/or Community Based
Communities
Organizations served
— Quantification of energy/non-energy benefits from
investments if applicable
(7) Energy Availability — Average outage duration
Energy — Planning reserve margin (resource adequacy)
Resiliency
Frequency of customer outages
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(8) Energy Generation — Percent of generation located in Washington or
Location connected to Avista transmission
(9) Residential — Number and percent of residential electric
Arrearages and disconnections for nonpayment
Energy Disconnections for
Security — Residential arrearages as reported to commission in
nonpayment (also Docket U-200281
found in Equity — Numbers and percent residential electric disconnects for
Area of non-payment by Named Community subset (Condition
Affordability) #22
(10) Outdoor Air Quality — Weighted average days exceeding healthy levels
— Avista plant air emissions
Environmental — Decreased use of wood heat for home heating
(11) Greenhouse Gas — Regional GHG emissions
Emissions — Avista GHG emissions
(12) Employee Diversity — Employee diversity representatives of communities
served by 2035
(13) Supplier Diversity — Supplier diversity at 11 percent by 2035
Public Health (14) Indoor Air Quality — Rank causes of indoor air quality (all and Named
(Condition #24) Communities
— Percentage of weatherization indoor air quality
measures all and Named Communities
While Avista is committed to ensuring the equitable implementation of the specific actions
identified in the 2021 CEIP and future CEIPs, there are circumstances where CBIs are
not applicable to the resource planning process. In circumstances where CBIs are
applicable to resource planning, Non-Energy Impacts (NEIs) and CBIs are utilized for
evaluation and selection. Additionally, CBIs may be applicable to program implementation
processes, which are outside the resource planning process. Figure 6 illustrates the
planning process for resource needs, how those resources are secured and implemented,
and how they impact the next IRP's load and resource needs. The applicability and timing
of CBI inclusion is described below. Avista measures and tracks the impact of business
decisions to focus on equitable outcomes.
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Figure 6: Planning Process
NeedsLoad
ReportMeasure/Track Available Resources
•
QuantifiedC131: Qualitative and CBl: Data
Availablegranular available
IRP Resource
N*40% Selection and 00e
Forecast
CBIs Applicable to Resource Selection
While most of Avista's CBIs are not related to resource planning, this section addresses
those CBIs related to resource planning. Avista's resource selection methodology uses
resource costs and benefits, the NCIF, CETA requirements, and NEI values to inform
resource outcomes, while avoiding any preconceived CBI targets or expectations.
Constraints or requirements can be created in the PRiSM model to ensure certain metrics
are met such as the PRM requirements or including financial incentives such as NEls to
incent certain decisions. These constraints may drive different outcomes as compared to
traditional planning. The following section outlines CBI forecasts, while the specific data
used to estimate the metrics and CBI values are included with the PRiSM model in the
2025 IRP Appendix G. These results can also be measured against a "Maximum
Customer Benefits" scenario and are achieved through increasing CBI values to
theoretical levels instead of cost-effective levels. In the end, it will be discretionary if
resource selection and the expected CBI outcomes are justified as equitable.
CBI No. 2— Number of Households with High Energy Burden
There are three forecastable metrics121 related to household energy burden included
within resource selection modeling, each excluding energy assistance funds:
121 Separate tracking on a forecasted basis for known low-income and Named Communities cannot be
completed until additional data is gathered.
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• The number of households with energy burden exceeding 6% of
income,
• Percentage of customers with excess energy burden, and
• Average excess energy burden.
To assess current and future energy burden, data for customer income, energy usage,
and energy rates is required. Customer income data was derived from a spatial analysis
of incomes reported to Avista by customers enrolled in programs with income limits,
census and third-party income data and was matched with usage and billing data. Total
energy burden includes all fuels, natural gas and electric, at a specific location.122
Forecasting this CBI requires assumptions regarding individual customer income and
usage along with the cost of non-electric household fuels. To forecast energy burden in
this analysis, customers are grouped by income, electric energy usage, and whether
customers have electric only or combined electric and natural gas services. Customer
income is escalated using the 2002-2022 historical income growth rate for each income
group and customer usage123 is forecasted using current energy use reduced by the
amount of energy efficiency selected for a specific income group.124 Lastly, the cost of the
energy used by the customer is estimated using a rate forecast based on the resources
selected through the IRP. The analysis does not consider additional energy assistance
beyond the assistance provided by the development of a low-income community solar
facility.
The first metric illustrates the forecast of the number of customers with excess energy
burden (see Figure 7) over the IRP planning horizon. These customers have a combined
energy bill between electric and natural gas exceeding 6% of their income to be included
in this metric. Customers can fall into this metric due to high usage or low income. In
2026, approximately 38,000 customers in Washington out of 250,000 will be energy
burdened. The absolute number of customers stays relatively flat until 2045, but as a
percentage of energy total, customers with energy burden decreases until 2045. The
increase in 2045 is due to high expected costs to comply with the 100% clean energy
standard when significant resources are retired, and additional clean generation is added
to ensure reliability and 100% clean energy in all hours. The 2045 costs are expected to
create a disproportional energy burden to lower income customers to pay for 100% clean
energy. To address this expected burden. Avista may not meet the 100% clean energy
target and seek compliance through CETA's cost cap through future CEIP processes.
Further, the main mechanism Avista can address this challenge is to deploy financial
energy assistance to energy customers, but given the potential need due to high costs of
meeting the 100% clean energy goal, energy assistance may reach 5% of revenue
122 Currently the only non-electric household fuel expense included is natural gas. Estimated costs for other
fuels such as fuel oil, propane, and wood should be included, but are not available at this time.
123 This analysis does not include EV load in the energy usage calculation as it would unfairly place higher
electric costs on the customer without considering other transportation costs not included in the calculation.
124 Typical increases to energy usage (i.e., adding new technology and devices) for this purpose is being
ignored.
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requirement cap. The only other ways to address energy burden within a resource plan
is to use energy efficiency to lower energy use and develop dedicated resources for low-
income customers. Both of these strategies are presumed in this plan, but all result in
financial energy assistance, further creating pressures on retail energy pricing.
Figure 7: WA Customers with Exces, Energy Burden (Before Energy Assistance)
70,000 25%
Percent of Customer with Excess Energy Burden
Number of Customers with Excess Energy Burden 21%
60,000
20%
18%
50,000 17% 17% 17%
to 16%
15% 15% 15% 15% 15% 15% 14% 14% 14% 14% 14% 14% 14% 1 15%
.�+ 40,000
to
7
U
30,000
r
10%
C
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a 20,000
to
5%
10,000
0 0%
(O 1­ 00 M O N CO V In (O n 00 M O N CO 7 LO
N N N NCI) (+) CO CO (M CM (M CO CO V V V V V V
O O O O Cl O O O O O O O O O O O Cl O O O
N N N N N N N N N N N N N N N N N N N N
The last customer energy burden metric is the amount of dollars per year of energy
assistance the customer would need to reduce their energy burden to achieve the 6%
level. The average excess energy burden growth is shown in Figure 8. This metric is
expected to increase both in nominal and real (2025 dollars) values though the real
increase is modest compared to the nominal increase at 1% a year above inflation. The
difference between the two demonstrates the impact of inflation compared to the impact
of rate increases.
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Figure 8: Average Washington Customer Excess Energy Burden
$2,000
$1,800 Average excess burden per household(nominal$)
-Average excess burden per household(Real$2025)
$1,600
$1,400
$1,200
$1,000
$800
$600
$400
O V O CO N V N (O V I� CD CO V N O 0)
$200 (o ca (o 0) v (O o CO co LO LO 00 r• (0 c rn
,­ (0 O O N M M M M M (n In In (O � 00 00 r
0) 0)
EH EA EH EH EH EH EH EH EH EH fH fH EH EH EH EH EH
$0
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(O r- W 0) O N M 7 (n CO h W M O N M 7 (n
N N N N CO M CO CO CO CO CO CO CO CO 7 7 7 7 7 V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
CBI No. 5— Named Community Clean Energy
This CBI monitors and prioritizes investments in DERs under 5 MW; specifically,
generation and storage resource opportunities in Named Communities. This CBI has
three metrics:
• Energy produced from DERs,
• DER energy storage capability, and
• Number of projects under 5 MW in Named Communities.
The 2025 IRP includes DER production and capacity, but identifying the number of
projects is outside the planning scope and cannot be accurately forecasted. There are
three methods for bringing these resources to the system. The first is through PURPA
development. Historically, this method has brought the most non-solicited energy to
Avista from developers building resources and selling the output to Avista using the
federal regulation requiring utilities to purchase the output from qualifying facilities at the
published avoided cost rates. The second method is from customers participating in
Avista's net metering program. These customer resources are behind-the-meter and the
energy produced is netted against their consumption.125 The amount of these resources
is outside of utility control and is based on whether the customer chooses to own their
own generation. The last category is small generation owned or contracted by Avista,
typically this includes community solar projects, but could also include other investments
from the NCIF or cost-effective resource additions typically selected through an RFP
process.
125 The amount of net metered generation in a Named Community was not available at the time of this
report.
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Named Community DER generation is shown in Figure 9 as the dark line. Most of the
historical DER generation is hydro-based and incremental additions are projected to be
from community solar projects funded by state incentives and Avista's NCIF, along with
a forecast for net metered generation as part of the DER forecast (2025 IRP Appendix F).
The orange line is the distributed energy storage forecast. In this case it is flat, as the IRP
did not identify any new projects. However, projects funded by the NCIF, or projects
determined by the Distribution Planning process, may increase this forecast. For
example, the NCIF is contributing funds for a 250 kW/ 500 kWh battery at the Martin
Luther King Jr. Center in Spokane, WA., along with a 100 kW of solar at the Family
Outreach Center with 150 kW backup natural gas generation. Updates to this project can
be found on Avista's website.126
Figure 9: Total MWh of DER in Named Communities
140,000 120
d
120,000 100
O 0
v! 100,000 U)
L C 80 w
3 O O �+
++2 80,000 m� L v
60 O Q.
O C 60,000 = V
(7 40 Z
40,000 cC
20,000 —Total MWh of DER<5 MW 20 C
—Total of MWh of DER energy storage<5 MW a)
0
C4 f— 00 M O N co V V) CD 1­ 00 O O N co V LO
N N N NM M m M CY) Cl) CY) M M M ItV V V V V
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
CBI No. 6— Investments in Named Communities
This plan includes high level estimates for investments and benefits in Named
Communities. This CBI includes three metrics:
• Incremental spending each year in Named Communities,
• Number of customers and/or CBOs served, and
• Quantification of energy/nonenergy benefits from investments (if
applicable).
To address these CBIs, Avista includes the annual utility invested cost of resources in the
2025 IRP and compares these values to the annual utility benefits and non-energy
impacts in Figure 10. The resources are selected based on a cost-effectiveness analysis
including utility benefits (energy/capacity) and NEls, except for the minimum spending
constraint from the NCIF. Resource selection choices are driven by high non-energy
126 https://www.mVayista.com/about-us/projects/mlk-community-center.
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impacts for energy efficiency in low-income areas. The total annual investments are
driven by energy efficiency projects. Investments peak in 2033127 and then decrease
thereafter as there are fewer energy efficiency opportunities.
This CBI includes a third metric accounting for the number or sites and projections of
future DERs. This forecast does not include this metric as the number of project sites will
be determined during implementation.
Figure 10: Named Community Investment and Benefits
$70
Annual Utility Benefits
$60 Annual NEI Benefits
$50 —Annual Investment
$40
N
c
$30
$20
$10
r F
$0
l0 1- 00 T O N M 1* In t0 f- 00 T O N M I In
N N N N M M Cl) Cl) Cl) Cl) Cl) M M M V V V 7 V d'
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
CBI No. 7— Energy Availability
This CBI is designed to ensure Avista has a reliable system for all customers including
Named Communities. It has three metrics:
• Average Outage Duration,
• Planning Reserve Margin (PRM) (Resource Adequacy), and
• Frequency of Customer Outages.
These metrics highlight customer reliability, but only one is related to resource planning.
The other two are impacted by distribution system reliability from delivery system issues.
The item applicable to IRP planning is the PRM where it is a minimum requirement for
resource capability during peak events. This metric is one of a few CBIs applying to the
full Avista system rather than just the State of Washington. Figure 11 shows the
forecasted expected peak hour resource capability versus load. The PRM is a forecast
comparing future peak loads and expected generation capability during peak hours using
127 2030 investment is nearly the same as 2029 due to the incremental energy efficiency in 2030 being
similar to 2029, but by 2031 investment increases again.
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QCC values.128 The PRM target for the resource plan is 24% in the winter and 16% in the
summer. As seen in this chart, the winter PRM goes below the target due to more reliance
on energy markets using the North Plains Connector transmission project beginning in
2033. Avista generally does not include market purchases in the PRM calculation
explaining the reduced value while maintaining reliability. If this project is completed,
Avista will increase its market power allowance and therefore result in lower PRM once
the project is complete. If the North Plains Connector project is delayed or cancelled, the
plan will be short capacity and alternative capacity resources will be required. Avista
addresses this risk with a scenario in the 2025 IRP Chapter 10, by requiring additional
energy storage.
Figure 11: Planning Reserve Margin
35%
V
-° 30%
■Winter ■Summer
0 25%
Q
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a 15%
R
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N N N N CO M M M M M CO M CO M V
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N N N N N N N N N N N N N N N N N N N N
CBI No. 8— Energy Generation Location
CETA encourages the use of local resources to enhance energy security. As such, this
CBI will address the following metric:
• Percent of generation located in Washington or connected to Avista's
transmission system.
To address energy security, Avista quantifies the amount of generation located within
Washington State or directly connected to Avista's transmissions system used for
customer needs. This metric is energy agnostic rather than clean energy focused. Figure
12 shows the IRP selected resource mix of energy created in either Washington or
connected to Avista's transmission system. The amounts are shown as a percentage of
total generation. New wind projects in Montana, outside Avista's system, keep the
forecast stable over time.
128 QCC values were derived by the WRAP with input from participating utilities and compiled by the
program administrator—SPP.
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Figure 12: Generation in Washington and/or Connected to Avista Transmission
100%
90%
80%
:r
70%
R
60%
d
CD 50%
0
40%
m
d 30%
IL
20%
10%
0%
(O co O O N M � In (O ti O O O N M (n
N N N N co M M M M M M M M M � It
O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
CBI No. 10— Outdoor Air Quality129
Avista's generation air emissions are forecastable within an IRP. The Outdoor Air Quality
CBI measures the following:
• Weighted average days exceeding healthy levels, and
• Avista's Washington plant air emissions.
The impacts of unhealthy days within local communities are typically related to events
outside of Avista's control and are after the fact calculations conducted by a third party.
From an IRP perspective the "weighted average days exceeding healthy levels" metric
cannot be forecasted in an IRP as multiple factors drive this metric, such as local weather
conditions and wildfires.
The forecastable metrics include S02, NOx, Mercury, and VOC emissions from Avista's
Washington based plants. These forecasts are based on emission rates per unit of fuel
burned. These emissions are regulated by local air authorities and plants meet all local
laws and regulations for air emissions and are found to be at levels safe for the local
population by the federal, state, and local regulating authorities. To ensure the emissions
129 The Company discussed the wood stove replacement program and proposed outdoor air quality metrics
with its EEAG during its October 2021 and 2022 sessions, and with its EAG during its February 2022 Equity
Lens session. The Department of Ecology joined the EAG's session to present outdoor air quality
monitoring availability options. No additional metrics were identified through these sessions. Avista
anticipates continued conversations with its advisory groups and the public pertaining to all CBls as it works
to develop its 2025 CEIP.
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are safe, plants must either add controls to reduce emissions or have daily or annual
operational limitations. Avista includes associated NEls to ensure air quality
improvements are considered in resource selection.
The Outdoor Air Quality metric measures total annual emission levels for Washington
State based thermal facilities including the Kettle Falls Generating Station (KFGS), Kettle
Falls CT, Boulder Park, and the Northeast CT. All metric results are forecasted to decline
over the IRP planning horizon due to lower expected thermal dispatch hours and potential
retirements of existing gas units through 2045 as shown in Figure 13. The significant
increase in 2045 is due to additional biomass generation forecasted to assist in meeting
the 100% clean energy target in 2045. Biomass generation is considered GHG neutral by
Washington law, but biomass does have other air emissions. Furthermore, NOx
emissions do not rapidly fall due to the forecasted need of green hydrogen-based fuels,
such as ammonia, to assist in meeting peak demand and replace aging natural gas
resources. The amount of NOx emissions will depend on technology and control systems
once turbine manufacturers make hydrogen-fueled resources commercially available
(post 2030) and the expected emissions from these plants will likely need to be revised
in future resource plans due to new technology to capture these emissions.
Figure 13: Washington Located Air Emissions
0.30
Sulfer Dioxide(S02) 0.010 Mercury(Hg)
0.009
0.25 0.008
V!
0.007
0.20
C C 0.006
12 0.15 9 0.005
V V
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0.10 0.003
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N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
Nitrogen Oxides(NOx) Variable Organic Compounds(VOC)
500 500
450 - - 450 -
400 400
y 350 y 350 -
C 300 C 300
250 250
200 200
150 150
100 100
50 50
O
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N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N N
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CBI No. 11 — Greenhouse Gas Emissions
There are two metrics for GHG Emissions covered in this section:
• Avista's GHG emissions, and
• Regional GHG emissions.
The first metric estimates the amount of direct emissions from Washington's share
(utilizing the PT ratio) of power plants and how those GHG emissions change considering
market transactions (labeled as "net emissions"). Figure 14 shows declining GHG
emissions due to additional clean energy resources expected to be added to the Western
Interconnect system and in turn will drive down the wholesale electric price and the need
for GHG emitting resources in as many hours as the past. Net emissions are lower than
direct emissions in the near-term as the calculation removes emissions related to power
sold off the system. Later in the planning horizon, when surplus system sales decrease,
Avista may need to purchase power causing net emissions to increase. This forecast
includes emissions associated with those purchases. This CBI may be modified in the
2025 CEIP to reflect the required methodology of reporting emissions for the CCA.
Figure 14: Washington Direct and Net Emissions
1.2
■Direct Emissions ■Net Emissions
1.0
N
C
0 0.8
.L
0.6
0
0.4co CD
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0.2 O O M M O O
(O fl- 00 O O N M 't tn CO I- 00 O O N M 't �
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O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N
One of CETA's main purposes is to reduce state level GHG emissions. Electric power
specifically related to eastern Washington is small in relation to total state emissions. The
goal of the regional GHG metric is to place Avista's emissions in the context of all
emissions allowing for a holistic analysis of GHG reductions. This CBI is to view the
effects of electrification in reducing emissions from other sectors. Most of the information
needed to track this CBI is not available on a regional basis or in a timely manner.
Additionally, the Avista cannot forecast emissions for industries outside of Avista. Due to
these factors, Avista will be proposing to remove this metric in its 2025 CEIP as it should
be tracked at the state level as part of statewide CBIs.
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Job Creation
Through the IRP's TAC and other customer engagement forums, an additional metric was
discussed to estimate the number of jobs created by IRP resource decisions. Avista
temporarily acquired the IMPLAN model to estimate economic benefits of new resources.
IMPLAN is an economic impact model designed to estimate the impacts of investments
in new generation or energy efficiency including job creation due to expected changes in
the local economy. This model was used to estimate permanent jobs per million-dollar
investment in each of the generation or energy efficiency technology areas of IRP
resources. Created jobs include both direct and induced jobs. The job creation results are
shown in Figure 15. This chart does not show lost jobs from resource retirements or for
alternative resource choices. Avista will not propose to make this a CBI in the 2025 CEIP
due to the significant cost to develop and maintain this metric and is reviewing alternative
methods to address job creation within the 2025 CEIP process.
Figure 15: Job Creation
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CBIs Not Applicable to Resource Planning
The following CBIs are not related to the resource planning phase and will be further
discussed in the 2025 CEIP. These items will be utilized in resource selection, program
implementation, or evaluation. In accordance with the 2021 CEIP Condition No. 35, the
following information is applicable to these CBIs.
CBI No. 1 — Participation in Company Programs
This CBI aims to increase overall participation levels for all customers in Avista's energy
efficiency and energy assistance programs, with special emphasis on Named
Communities. While the priority is to increase participation within Named Communities
specifically, Avista will also consider the current participation levels in energy efficiency
and energy assistance programs of all Washington customers as part of its baseline when
measuring how participation increases. The intent of these efforts is to prioritize
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distributional equity by helping to address direct or indirect barriers impacting a
customer's ability to participate in energy efficiency or energy assistance programs.
This metric emphasizes overall participation; however, the impact of these efforts is
directly related to reducing customers' overall energy burden and making energy more
affordable. Energy efficiency and energy assistance efforts have known energy and NEI
values with direct benefits to customers from both affordability and overall wellbeing.
When combined with CBI No. 3 concerning availability of communication, Avista can
monitor the successful steps contributing to increased participation. The Company will
monitor the following metrics included in this CBI:
• Participation in weatherization, efficiency, and energy assistance
programs for all customers and Named Communities,
• Saturation of energy assistance programs for all customers and
Named Communities, and
• Residential appliance and equipment rebates provided to customers
residing in Named Communities and rental units (Condition No. 17).
Tracking the metrics for CBI No. 1 requires data for individual customers, as well as each
customer in a Named Community. This requires extensive data analysis utilizing Avista's
Customer Care and Billing system (CC&B). In IRP planning, energy efficiency is
forecasted based on a total energy savings by program type and by customer segment
(i.e., residential and commercial customers) not at the customer level. Avista's advisory
groups, such as the Equity Advisory Group (EAG), Energy Assistance Advisory Group
(EAAG), and Energy Efficiency Advisory Group (EEAG) will continue to be instrumental
in developing a method for prioritizing energy efficiency and energy assistance programs
to ensure they are equitably distributed.
CBI No. 3—Availability of Method/Modes of Communication
CBI No. 3 focuses on increasing access to clean energy and reaching customers who
have not participated in Avista's energy efficiency and energy assistance programs due
to language barriers or other limitations, such as not knowing about the programs or
understanding the application process. Increased outreach should increase participation
which will lead to lower energy usage and costs, while positively impacting accessibility
and affordability. This CBI seeks to increase participation in energy efficiency and energy
assistance programs by improving how customers hear about these programs. The
metrics for this CBI are:
• Number of outreach contacts,
• Number of marketing impressions, and
• Translation services.
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Barriers may limit access to participation in Company programs and make it more difficult
and expensive for customers in Named Communities to receive assistance. Increased
and expanded customer outreach will grow energy efficiency and energy assistance
participation making energy service more affordable. Further, increased energy efficiency
participation benefits all customers by reducing the need for more generation. This CBI
is not relevant to resource planning but rather to program implementation. Avista
continually works with its advisory groups to improve upon its methods and modes of
communication to increase participation.
CBI No. 4— Transportation Electrification
CBI No. 4 considers Transportation Electrification efforts and the impacts on customers
in Named Communities. Avista's Transportation Electrification Plan (TEP)130 provides a
path to a cleaner energy future by 2045 by electrifying transportation. The TEP outlines
guiding principles, strategies, and an action plan with detailed program descriptions, cost
and benefit estimates, and regular reporting details. The TEP has an aspirational goal of
investing 30% of Avista's total transportation electrification spend on programs benefiting
Named Communities. Avista's Tariff Schedule 77 and the TEP commit to regular reporting
of Transportation Electrification (TE) efforts through several metrics.
Avista will track transportation electrification in Named Communities with three metrics:
• Annual trips provided by Community Based Organizations (CBOs)
using electric transportation,
• Annual passenger miles provided by CBOs using electric
transportation, and
• Public charging ports available in Named Communities.
The impacts of transportation electrification are embedded in Avista's load forecast and
resource planning processes. Program implementation requires focus on where the
impacts of efforts will be located. Avista will continue collaboration with its advisory groups
and collaborating with CBOs to ensure a focus on Named Communities throughout the
TEP implementation process.
CBI No. 7— Energy Availability
CBI No. 7 aims to ensure customers in Named Communities are not disproportionally
impacted by delivery system or resource adequacy power outages due to their socio-
economic or sensitivity factors. This CBI tracks the location of outages and will inform
future implementation and system development to minimize the potential for outages.
Avista will measure the following metrics:
• Average Outage duration by Customer Average Interruption Duration Index
(CAIDI) - Not included in resource planning,
130 UTC Docket UE-200607, acknowledged by the Washington UTC on October 15, 2020.
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• Frequency of Customer Outages by Customer Experiencing Multiple Interruptions
(CEMI) - Not Included in resource planning, and
• Planning Reserve Margin (Resource Adequacy) - Included in resource planning.
Avista has a duty to provide safe and reliable energy to its entire customer base. Historical
customer outage information provides customers with a measure of resiliency and
reliability by calculating the time it takes to restore a customer's service from an outage
but does not include the cause of the outage. Most outages are related to the distribution
system and service can be interrupted by weather, equipment failure, maintenance, or
other factors. Monitoring these two metrics will provide data to inform Avista where new
distribution resources may be located to best address inequities. The newly formed
Distribution Planning Advisory Group (DPAG) will provide insight into this distribution
planning process.
CBI No. 9— Residential Arrearages and Disconnections for Non-Payment
CBI No. 14 tracks residential arrearages and disconnections for non-payment.
Connection to energy service was identified by interested parties as a key element of
energy security. This CBI is not applicable to resource planning. For planning purposes,
a certain level of price elasticity is included relating to the cost of resource selection and
may ultimately impact arrearages and disconnections for non-payment. Resource
decisions include the cost of arrearages, while energy efficiency evaluations include these
savings by way of the NEI. Reporting this CBI keeps the issue at the forefront of
affordability and/or energy burden conversations during implementation of future
investments. Avista includes a utility NEI for a decrease in contact center calls for certain
low-income energy efficiency measures to account for reductions in future disconnects.
CBI No. 12— Employee Diversity and No. 13 Supplier Diversity
The purpose behind CBIs No. 11 and No. 12 are to generate awareness and to promote
recognitional equity. Tracking employee and supplier diversity is a first step in recognizing
the potential of systemic racism embedded within existing processes and procedures.
Tracking these metrics will result in an increased focus towards identifying and changing
policies to increase employee and supplier diversity to help eliminate inequities. This CBI
is not intended to be utilized as a resource planning metric; however, as an
implementation tool Avista includes diversity metrics in its selection criteria for resource
selection as part of long-term resource procurement.
The EAG raised ending systemic racism as a major concern and discussed what Avista
could do to help with this wide-ranging issue. CBI No. 11 is an initial attempt to track and
improve Avista's employee diversity to match the diversity and genders of the
communities it serves. This aspirational goal will be tracked by craft, non-craft, managers
and directors, and executives for race and gender with a goal of matching the
communities being served by 2035. CBI No. 12 focuses on the supplier side of diversity
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to help make the diversity of our suppliers closer to the communities we serve.
CBI No. 14— Indoor Air Quality
In accordance with Avista's CEIP Condition 24, in its 2023 Biennial CEIP Update, it
proposed and received approval to apply a new CBI for energy efficiency programs that
helps to identify, measure, and apply metrics to existing low-income weatherization
programs and energy efficiency programs. The Indoor Air Quality (IAQ) metrics are part
of a Health and Safety NEI used to assess economic, health, and environmental burdens.
The health and safety metrics include HVAC mechanical ventilation, natural ventilation,
air infiltration, indoor air pollution contributors, and overall health and safety total home
assessments. Based on the Washington Department of Commerce and ASHREA's 62.2
standard for low-income weatherization program metrics, Avista is now tracking the
following data for this metric:
• Ranking of causes of IAQ (within & outside Named Communities),
• Percentage of weatherization IAQ measures (within & outside Named
Communities).
Avista is currently tracking data for these metrics and will provide its first set of data in its
2025 CEIP.
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