Item 3- Briefing Modeling Results for Resource, Generation, and Climate Protection Plan — original pdf

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Resource, Generation and Climate Protection Plan to 2035 Briefing and Process Update Lisa Martin Deputy General Manager and Chief Operating Officer September 30, 2024 © Austin Energy Important Context for this Discussion Models provide information not a specific plan or recommendation The following slides show data results associated with preliminary modeling efforts for the Resource, Generation and Climate Protection Plan to 2035. These results do not reflect a recommendation, and they do not reflect a plan. These results are for informational purposes only. All modeling reflects the input assumptions coordinated with the Electric Utility Commission earlier this year. 2 Agenda General Reminders Recap of Modeling Timeline Austin Energy – Modeling Results Ascend Analytics – Modeling Results Discussion & Collaboration 3 General Reminders • 17 portfolios studied to date • 13 Austin Energy & EUC-defined portfolios • 4 Ascend Analytics (software-optimized) portfolios • Several portfolios included for reference only • Edge cases, purposefully defined to help understand the boundaries • Slides show raw data for comparison across portfolios • We're not drawing conclusions Portfolio Evaluation • With these portfolios, tradeoffs are significant • With the information gained from these portfolios, we will need to refine • Next step: Ask "what if?" and refine portfolios by mixing different technologies, seeking a more acceptable set of tradeoffs PORTFOLIO A PORTFOLIO B PORTFOLIO C PORTFOLIO D PORTFOLIO E PORTFOLIO F Refine Portfolios 4 EUC Office Hours • Tuesday, Oct. 1 1 p.m. – 3 p.m. • Wednesday, Oct. 2 11 a.m. – 1 p.m. • Thursday, Oct. 3 2:30 p.m. – 4 p.m. • Friday, Oct. 4 10 a.m. – 12 p.m. If none of the above times work, please let us know so we can find a time to collaborate. Office Hours Objectives: • Review detailed results • Ask questions • Determine takeaways • Refine portfolios 5 Modeling Timeline Modeling Framework to EUC 7/10/24 Portfolios + Scenarios to EUC 8/8/24 Ascend Modeling Overview to EUC 9/9/24 Modeling Results #1 to EUC 9/30/24 Modeling Results #2 to EUC October 2024 JUNE JULY AUG SEPT OCT Data Sources 7/8 Webber Draft Report 7/31 DNV Study Preliminary Results 1st Model Runs 2nd Model Runs 7/15 EUC Input on Framework 8/12 EUC Input on Portfolios + Scenarios 10/1 – 10/4 EUC Office Hours to Refine Portfolios 6 Portfolio Modeling Results Austin Energy Resource, Generation and Climate Protection Plan to 2035 Michael Enger Vice President, Energy Market Operations & Resource Planning September 30, 2024 © Austin Energy Important Context for this Discussion Models provide information not a specific plan or recommendation The following slides show data results associated with preliminary modeling efforts for the Resource, Generation and Climate Protection Plan to 2035. These results do not reflect a recommendation, and they do not reflect a plan. These results are for informational purposes only. All modeling reflects the input assumptions coordinated with the Electric Utility Commission earlier this year. 8 Reference Guide to Numbered Portfolios REF # PORTFOLIO DESCRIPTION 1 2 3 4 5 6 7 8 9 10 11 12 13 No New Commitments Existing DSM commitments, no new generation 2030 Current Plan 100% Carbon-Free by 2035, 65% Renewables by 2027, existing DSM commitments, REACH on gas Local Gen/Storage + Margin 575 MW new local peakers and combined cycle starting 2027, 275 MW local storage, 100% DNV projections*, replace PPAs, Decker/SHEC run through 2035 Local Dispatchable + Margin 1,100 MW new local peakers & combined cycle starting 2027, 50% DNV projections, REACH on FPP, Decker/SHEC run through 2035 Retire Decker in 2027, 100% DNV projections, 100% CF, 65% RE, REACH on gas, retire SHEC 2034 Meet Env Goals + Expand DSM Aggressive DSM + Storage + Keep PPAs Aggressive DSM + Storage + 65% RE Goal Aggressive DNV projections, replace PPAs,100% CF, REACH on gas, retire Decker/SHEC 2034 Aggressive DNV projections, 65% RE, 100% CF, REACH on gas, retire Decker/SHEC 2034 Hydrogen-Capable Local Plant 1,100 MW local hydrogen-capable peakers starting in 2030, 100% DNV projections, 100% CF, 65% RE, REACH on gas, retire Decker/SHEC 2034 Hydrogen + Local Storage 550 MW local hydrogen peakers, 395 MW local storage, 100% DNV projections, 100% CF, 65% RE, REACH on gas, retire Decker/SHEC 2034 Keep Existing Gas + Local Storage Decker/SHEC run past 2035, 395 MW local storage, 100% DNV projections, 65% RE, REACH on gas Replace FPP in 2028 w/Gas FPP retire end of 2028, 575 MW new local peakers and combined cycle, 100% DNV projections, 65% RE, REACH on FPP and gas EUC – 1 (Working Group Recs) 525 MW local storage, 700 MW local solar, 540 MW new EE, 300 MW DR, 100% RE as % of load, 100% CF, REACH on gas, retire Decker/SHEC 2034 EUC – 2 925 MW local storage, aggressive DNV projections,100% RE as % of load, 100% CF, REACH on gas, retire Decker/SHEC 2034 *DNV projections refers to the quantities of Demand-Side Management (Demand Response, Energy Efficiency, and Local Solar) resulting from the market potential study performed by DNV Energy Insights 9 Glossary of Terms Term Definition Ascend Analytics Consultant currently providing additional modeling support – Ascend’s modeling uses the same set of DNV Study inputs and assumptions as AE’s UPLAN modeling, but the main difference in their approach is that their software designs optimized portfolios based on constraints and UPLAN relies on the modeling team to design the portfolios DNV is a consultant that is currently working on a demand-side management market potential study for Austin Energy – preliminary data from DNV related to Austin’s market potential for additional local solar, demand response and energy efficiency is included in the modeling – “100% of DNV study” indicates that a portfolio includes 100% of the additional DSM savings based on DNV’s data Local Congestion When transmission lines that bring power into the Austin Energy service territory begin to reach their maximum carrying capacity, they experience “congestion” which can cause cost increases and potential reliability issues Local vs. Non- Local Generation An asset is considered “local” generation if it is physically located within the Austin Energy service territory – this is important in the context of relieving “local congestion” (see definition above) Portfolios Scenarios UPLAN A specific mix of electricity generation and demand-side management resources year by year over the modeling period of 2025-2035, provided in MW capacity Different possible future worlds with different kinds of stressors (extreme events, local congestion, ERCOT market rule changes) that test each portfolio’s performance in that future through modeling Modeling software used by Austin Energy to simulate how a portfolio of resources will perform operationally and financially under projected normal conditions and in various future states (scenarios) 10 Demand-Side Management 2035 Austin Energy 2035 Commitments & Market Penetration Study Projections s t t a w a g e M 1200 1000 800 600 400 200 0 149 120 99 332 360 Demand Response Local Solar Energy Efficiency Austin Energy Existing Commitment - 2035 DNV Study Projection of Achievable - Additional 2035 Note: All new MW capacity figures provided in graph represent cumulative additions projected by 2035. Energy Efficiency figures do not include pre-2024 installations (~828 MW). 11 248 812 TOTAL Portfolio Comparison – Financial Impacts 12 Portfolio #5 – Meet Environment Goals + Expand DSM Installed Capacity (MW) Output Metric Value Rank NPV Net Cost ($millions) (Normal/Avg of Scenarios) 2035 Bill Increase ($/Month) Liquidity Risk Reliability Risk Hours (2035) Total CO2 (Million Metric Tons) Total NOx (Metric Tons) $10,480/ $13,029 $68.30 $1.63B 2115 5.8 599 10 10 12 9 6 6  FPP Retires:  Decker/SHEC Retire:  New Local Solar* (MW):  New Local Storage (MW):  New Local Gas (MW):  DSM Projection:  RE Goal:  100% Carbon-Free Goal: *includes existing commitments 2024 2027/2034 431 0 0 DNV Study 65% Yes 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 - 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 Demand Response Energy Efficiency FPP Coal Sand Hill CT NG CC Community Solar Non-Local Wind Local 12-hr NAC Biomass Decker CT NG CT Non-Local Solar STP Nuke Sand Hill CC NG-H2 CT Customer-Sited Solar Non-Local Solar (New) Non-Local Wind (New) Local 100-hr Local 4-hr Local 2-hr 13 Net Cost  “Net Cost” = Total capital + O&M costs to generate power – Total revenue from sale of power for a given portfolio mix.  Capital costs for new assets amortized (spread out evenly) over expected life of asset.  O&M costs include fuel, personnel, regular maintenance, etc.  To compare a single “Net Cost” value across portfolios we use the Net Present Value (NPV) of the annual net costs for the 20-year period 2025-2045 using 7.8% discount rate. 14 Net Present Value of 20-Yr Annual Net Costs Normal Conditions Reference Portfolios n o i l l i B $ 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 - 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 15 Net Present Value of 20-Yr Annual Net Costs Normal Conditions Extreme Weather Scenario High Congestion Scenario Market Rules Change Scenario Reference Portfolios n o i l l i B $ 25.0 20.0 15.0 10.0 5.0 - 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 16 Bill Impact  "Average Monthly Residential Bill Increase" = expected increase in a typical Austin Energy residential customer's monthly electricity bill in 2035 compared with today due to the additional net costs associated with the generation portfolio only.  Based on the "Net Cost" of each portfolio.  Does not account for any other new or required AE capital or O&M costs in the future. 17 2035 Average Monthly Residential Bill Increase Reference Portfolios h t n o M / $ $140 $120 $100 $80 $60 $40 $20 $- 1 2 3 4 5 6 7 8 9 10 11 12 13 Portfolio # Normal Conditions Extreme Weather Scenario High Congestion Scenario Market Rules Change Scenario 2035 2% Affordability Target DISCLAIMER: These are representative results based on modeling for the 2035 Resource Generation Plan and are not projections of Austin Energy's future prices. The results are not inclusive of factors beyond the scope of this Resource Generation Plan modeling. 18 Avg. Monthly Bill Impact by Year – Avg. of All Scenarios $90 $80 $70 $60 $50 $40 $30 $20 $10 $- $(10) 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 DISCLAIMER: These are representative results based on modeling for the 2035 Resource Generation Plan and are not projections of Austin Energy's future prices. The results are not inclusive of factors beyond the scope of this Resource Generation Plan modeling. 13 12 7 5 6 2 9 8 1 3 4 10 11 19 Electricity Burden  “Electricity Burden” is the percentage of a household’s monthly income that goes toward their electricity bill  A higher percentage of income dedicated to electricity costs indicates a higher “electricity burden” for that household  For this analysis AE estimates the electricity burden for a typical customer in its Customer Assistance Program (CAP) using the 2023 Federal Poverty Income guidelines as a reference for estimated annual income 20 2035 Estimated Customer Assistance Program (CAP) Customer Electricity Burden (Avg of Scenarios) Reference Portfolios 6.0% 5.0% 4.0% n e d r u B y t i c i r t c e l E 3.0% 2.0% 1.0% 0.0% 1 2 3 4 5 6 9 10 11 12 13 7 Portfolio # 8 2035 Estimated CAP Customer Electricity Burden 2023 Estimated CAP Customer Electricity Burden 2023 State of Texas Average Low Income Customer Electricity Burden 21 Liquidity Risk  “Liquidity Risk” = Risk to Austin Energy of not having enough cash on-hand to settle financial account with ERCOT after an extreme event.  Uses a modeling technique called “backcasting” to estimate how a portfolio of resources would have performed financially during an event similar to Winter Storm Uri.  During an extreme event, ERCOT prices can spike – Austin Energy must purchase power from ERCOT to cover local load – if Austin Energy does not sell enough electricity at the same prices to cover expense, it must pay the difference to ERCOT immediately.  Based on portfolio mix in 2035. 22 Stress Test Results – Total Liquidity Risk Based on 2035 portfolio mix Reference Portfolios n o i l l i B $ 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 23 Portfolio Comparison - Reliability Impacts 24 Reliability Risk Hours  “Reliability Risk Hours” = total number of hours in a given year that the model predicts there will be increased risk of local outages.  Local outages in this case are a result of not enough electricity physically available to meet Austin’s load.  Can be caused by high local load, decrease in local power generation, decrease in import capacity, or a combination of these factors. 25 2035 Reliability Risk Hours One year = 8,760 hours Reference Portfolios 3,000 2,500 2,000 1,500 s r u o H 1,000 500 - 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 26 2035 Reliability Risk Events of 4,6 or 8 Hours Reference Portfolios s t n e v E f o # 60 50 40 30 20 10 - 1 2 3 4 5 6 8 9 10 11 12 13 7 Portfolio # 27 Portfolio Comparison – Emission Impacts 28 Modeled Austin Energy Stack CO2 Emissions By Year vs. Historical 2 O C s n o T c i r t e M 7,000,000 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 - 2 0 0 5 2 0 0 7 2 0 0 9 2 0 1 1 2 0 1 3 2 0 1 5 2 0 1 7 2 0 1 9 2 0 2 1 2 0 2 3 2 0 2 5 2 0 2 7 2 0 2 9 2 0 3 1 2 0 3 3 2 0 3 5 Historical Portfolio # 11 10 4 3 1 2 5 6 7 8 9 12 13 2035 % Reduction (Relative to 2020) -0.2% 28% 49% 64% 85% 100% 100% 100% 100% 100% 100% 100% 100% 4 3 11 1 10 2 5 6 7 8 9 12 13 29  2 O C s n o T c i r t e M n o i l l i M 45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 - 14.3 Total CO2 Emissions (Million Metric Tons) 2025-2035 Reference Portfolios 40.4 26.6 24.5 5.8 5.8 5.7 5.6 9.0 8.2 6.3 1 2 3 4 5 6 8 9 10 11 7 Portfolio # 4.3 12 4.4 13 30 Percent of Load Matched with Carbon-Free Energy in 2035 Range Accounts for Curtailments Reference Portfolios d a o L f o e e r f - n o b r a C % 120% 100% 80% 60% 40% 20% 0% 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 31 Total NOx Emissions (Metric Tons) 2025-2035 10,000 Reference Portfolios x O N s n o T c i r t e M 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 - 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 32 Emissions 2025-2035 Total SOx Total Particulate Matter (PM) Reference Portfolios Reference Portfolios 1,100 1,000 x O S s n o T c i r t e M 900 800 700 600 500 400 300 200 100 - M P s n o T c i r t e M 1000 900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 9 10 11 12 13 1 2 3 4 5 9 10 11 12 13 6 7 Portfolio # 8 8 7 6 Portfolio # 33 Summary Tables with Overall Values and Rankings 34 Portfolio Net Cost 20-yr NPV ($MM) 2035 Bill Impact ($/Month) 2035 Energy Burden (%) Total Liquidity Need ($MM) 2035 Reliability Risk Hours (Hours) Total CO2 Emissions (Million Metric Tons) Total NOx Emissions (Metric Tons) Total SOx Emissions (Metric Tons) Total PM Emissions (Metric Tons) 2035 Reliability Risk Events 4+ Hours (Count) 9 1 2 3 4 5 6 7 8 9 10 11 12 13 $9,771 $13,026 $8,659 $7,336 $13,029 $12,913 $13,053 $10,629 $11,665 $12,155 $9,273 $13,244 $14,315 $38 $67 $33 $21 $68 $68 $69 $43 $55 $56 $35 $75 $81 3.7% 4.5% 3.5% 3.2% 4.5% 4.5% 4.5% 3.8% 4.1% 4.1% 3.6% 4.7% 4.9% $1,291 $1,685 $424 $365 $1,657 $1,643 $1,445 $653 $961 $549 $359 $1,111 $1,313 17 0 0 20 25 24 0 20 4 0 55 56 165 2,204 0 0 2,115 2,141 2,136 3 438 41 0 1,369 2,449 14 6 27 40 6 6 6 9 8 6 25 4 4 1596 589 3016 8978 599 584 573 1730 1355 650 5267 440 457 1036 49 8 88 7 4 4 20 17 4 562 0 1 389 152 761 869 153 150 148 259 235 554 167 114 118 35 Portfolio Net Cost 20-yr NPV 2035 Bill Impact 2035 Energy Burden Total Liquidity Need 2035 Reliability Risk Hours Total CO2 Emissions Total NOx Emissions Total SOx Emissions Total PM Emissions 2035 Reliability Risk Events 4+ hours 6 11 10 7 1 1 8 1 8 5 1 12 13 6 12 11 10 1 1 9 4 7 5 1 8 13 8 13 3 2 12 11 10 5 6 4 1 7 9 10 5 12 13 6 4 3 9 8 7 1 2 9 5 11 13 10 6 4 3 8 7 1 2 10 7 11 13 6 3 3 9 8 3 1 2 10 5 12 13 6 4 3 9 8 7 1 2 11 11 12 12 1 2 3 4 5 6 7 8 9 10 11 12 13 10 8 11 4 9 2 1 5 6 7 3 12 13 10 9 11 4 8 2 1 5 6 7 3 12 13 10 9 11 4 8 2 1 5 6 7 3 12 13 Ranks each portfolio 1-13 (1 = best, 13 = worst) within each output metric column 36 ©Austin Energy. All rights reserved. Austin Energy and the Austin Energy logo and combinations thereof are trademarks of Austin Energy, the electric department of the City of Austin, Texas. Other names are for informational purposes only and may be trademarks of their respective owners. Portfolio Modeling Overview Austin Energy Modeling Process Utilizing UPLAN and PowerSIMM modeling tools to evaluate the performance of multiple human-made portfolios across various scenarios. 3rd Party Modeling Process Ascend’s resource planning methodology and modeling tools generate optimized portfolios based on specified constraints. Portfolio Evaluation All modeling results will be evaluated to select portfolios for further consideration. PORTFOLIO A PORTFOLIO B PORTFOLIO C PORTFOLIO D PORTFOLIO E PORTFOLIO F Shortlist of Portfolios 38 EVALUATING OPTIONS FOR AUSTIN ENERGY'S PORTFOLIO THROUGH 2035 Benjamin Anderson Manager of Resource Planning September 2024 Introduction 40 Introduction: Austin Energy's Resource, Generation and Climate Protection Plan to 2035 Analysis Goal: Evaluate four generation portfolios that illustrate the tradeoffs between costs, emissions and reliability during the period of 2025-2035. Austin Energy commissioned Ascend Analytics to conduct this resource planning study. Results will supplement Austin Energy’s Uplan analysis, to inform which portfolios are down-selected for further study. Ascend used the same cost and load assumptions as Austin Energy's Uplan analysis. Purpose Methodology Using its flagship PowerSIMM software, Ascend ran a capacity expansion model with different constraint sets to create four portfolios and ran these portfolios through production cost model to evaluate their costs, emissions, and reliability. Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 41 Modeled Portfolios 42 Overview of the Portfolios Portfolio A (Baseline) • Meets emissions and renewable • • energy targets Builds sufficient local firm capacity to cover peak loads Least-cost path to meet the constraints Portfolio C • No emissions or renewable targets • Builds sufficient local firm capacity to cover peak loads Portfolio B • Meets same emissions, renewable, and local firm capacity targets as Portfolio A, but without any new gas or hydrogen-burning plants Provides a path to zero emissions not dependent on clean hydrogen availability • Portfolio D • Meets the same emissions and renewable targets as Portfolio A Builds sufficient local firm capacity to cover peak loads plus a 15% margin • Portfolios A, B, & D are carbon-free by 2035 and achieve 65% renewable energy from 2027 onwards. The Portfolios must build local storage or gas/hydrogen-fueled power plants to satisfy the local firm capacity constraint. All portfolios include max assumptions about demand-side management buildouts from the DNV study, including the following by 2035: • • • • 360 MW of energy efficiency 270 MW of demand response 371 MW of customer-sited solar 60 MW of community solar (Portfolio B builds additional) Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 43 Portfolio Constraints A B C D Coal-Free Portfolio: FPP is not included in the portfolio (assumes retirement 12/31/2024) Carbon-Free (annual emissions requirement): Starting with 2023 carbon emissions, ramp down linearly to zero in 2035 65% Renewable (annual renewable energy requirement): Ensure renewable energy production is at least 65% of load in 2027 and beyond Green Hydrogen (conversion requirement): All new and existing natural gas plants convert to green hydrogen fuel in the 2030s Local Reliability: Ensure local firm capacity (ELCC adjusted) plus import capacity exceeds annual peak load Enhanced Local Reliability: Ensure local firm capacity (ELCC adjusted) plus import capacity exceeds annual peak load with 15% margin No New Natural Gas or Hydrogen: Prevents new natural gas or hydrogen units from satisfying local reliability requirement Reduced Natural Gas Dispatch (REACH requirement): Applies a REACH adder to existing natural gas plants and retires the units at the end of 2034 No Fuel Restrictions: Allows continued operation of natural gas plants without hydrogen conversion 44 Ascend's Capacity Expansion Model Ascend's capacity expansion model takes forecasts of load, weather, and market prices as inputs. It receives a set of technologies that can be built, and constraints that it must meet (including emissions, renewables, and reliability targets). It finds the cost-optimal resource buildout that satisfies these constraints. Cost Emissions Reliability Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 45 Portfolio Results 46 Portfolio A: Balancing Cost, Emissions, and Reliability Buildouts: Wind PPA procurements, new gas buildouts, and conversion of both existing and new gas to hydrogen Installed Capacity (MW) • 1885 MW of wind PPAs are procured to satisfy the 65% renewable energy target • 630 MW of new, local, hydrogen- capable peakers built for reliability • Sand Hill, Decker, and new peakers are converted to burn hydrogen in the 2030s and achieve zero carbon emissions by 2035 6000 5000 4000 3000 2000 1000 0 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 STP Nuke Decker CT Central Solar NAC Biomass NG-H2 CT West Solar Sand Hill CC Customer-Sited Solar South Wind Sand Hill CT Community Solar West Wind Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 47 Portfolio B: Reaching Zero Emissions with Renewables and Batteries Buildouts: Wind PPA procurements, local solar and storage buildouts, and the retirement of all gas-fired units provide a way to reach zero emissions without green hydrogen Installed Capacity (MW) • 1885 MW of wind PPAs are procured to satisfy the 65% renewable energy target • 2750 MW of local storage, charged by 2800 MW of community solar, provides local energy and capacity • REACH adders were added to Sand Hill and Decker. They reduce runtime, leading to lower emissions, and retire in 2034. 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 48 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 STP Nuke Decker CT West Solar Local 4-hr NAC Biomass Sand Hill CC Sand Hill CT Customer-Sited Solar Community Solar Central Solar West Wind Local 12-hr South Wind Local 2-hr Portfolio C: Economical and Reliable, but with High Emissions Buildouts: Only economic wind PPAs are procured. A local CC and several peakers are built for reliability. Sand Hill and Decker don't retire or convert. Installed Capacity (MW) • 400 MW of economic wind PPAs are procured • 400 MW of local peakers are built for reliability. A 200-MW, local CC is built for reliability. • Sand Hill and Decker run on gas and don't retire • FPP runs until end of 2031 6000 5000 4000 3000 2000 1000 0 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 STP Nuke Sand Hill CT FPP Coal Decker CT Customer-Sited Solar Community Solar Central Solar South Wind West Wind NAC Biomass Sand Hill CC NG-H2 CC NG-H2 CT West Solar Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 49 Buildouts: Wind PPA procurements, increased new gas buildouts, and conversion of both existing and new gas to hydrogen provide a clean portfolio with enhanced reliability Installed Capacity (MW) Portfolio D: Enhanced Reliability • 1885 MW of wind PPAs are procured to satisfy the 65% renewable energy target • 1,155 MW of new, local, hydrogen- capable peakers built for enhanced reliability • Sand Hill, Decker, and new peakers are converted to burn hydrogen in the 2030s and achieve zero carbon emissions by 2035 7000 6000 5000 4000 3000 2000 1000 0 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 STP Nuke Decker CT Central Solar NAC Biomass NG-H2 CT West Solar Sand Hill CC Customer-Sited Solar South Wind Sand Hill CT Community Solar West Wind Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 50 • In Portfolios A, B, & D, wind and solar provide 2035 Installed Capacity (MW) Portfolio Buildouts most of the energy by 2035 • West and South wind are the primary renewables selected due to their lower net costs. • Portfolios A, C, & D build local peakers and CCs to provide reliability, whereas Portfolio B uses local storage and solar • Portfolio A has 1,330 MW of local generation, whereas Portfolio B has 5,631 MW. • Numbers for this graph are in a table in the Appendix 12000 10000 8000 6000 4000 2000 0 A B C D Demand Response Energy Efficiency STP Nuke NAC Biomass Decker CT Sand Hill CC NG-H2 CC West Solar Local 12-hr South Wind Local 4-hr Sand Hill CT NG-H2 CT West Wind Local 2-hr Customer-Sited Solar Community Solar Central Solar Portfolios A, B & D have more buildouts than Portfolio C to achieve the renewable energy target Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 51 Costs, Emissions, & Reliability 52 Portfolio Costs • Portfolio A: A steady increase in net costs from building new peakers, converting peakers and CCs to hydrogen, and procuring wind PPAs • Portfolio B: Most expensive option, with most costs coming from battery tolls and community solar • Portfolio C: Having plants burn gas and only procuring economical PPAs yields the lowest-cost portfolio, but is the only one with carbon and SO2 emissions in 2035 • Portfolio D: Similar to Portfolio A. Increased peaker buildout has roughly equal cost and revenue. $16 $14 $12 $10 $8 $6 $4 $2 $0 Net Portfolio Cost NPV, 2025-2045 ($B) $14.08 $6.78 $5.55 $6.90 Rates* increase marginally from 9.5c/kWh in 2025 to 12-13c/kWh in 2035, for Portfolios A, C, & D. Portfolio B has much higher rates: 20c/kWh in 2035. A B C D 5th Percentile 95th Percentile Cost *DISCLAIMER: these are representative results based on modeling for the 2035 Resource Generation Plan and are not projections of AE's future prices. The results are not inclusive of factors beyond the scope of this modeling. These rates are not comparable to bill impact for Uplan analysis. Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 53 Portfolio Costs Continued Cost Metric Portfolio A Portfolio B Portfolio C Portfolio D 2035 Rates ($/kWh) 0.132 0.202 0.121 0.133 2025-2045 NPV ($B) Net Costs Mean Net Costs P5 Net Costs P95 Load Costs Levelized Capital Costs O&M costs Revenue $6.78 $5.90 $7.76 $6.70 $0.36 $6.15 $6.43 $14.08 $13.33 $14.77 $6.70 $4.37 $10.55 $7.55 $5.55 $4.18 $6.91 $6.70 $0.34 $4.07 $5.56 $6.90 $5.94 $7.81 $6.70 $0.61 $6.25 $6.66 Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 54 Portfolio Emissions • Emissions are significantly reduced by 2030 in Portfolios A, B, & D, as gas plants convert to hydrogen or operate at low capacity factors • Compared to Portfolio A, cumulative emissions decrease 68% in B, more than double in C, and increase 9% in D • In 2035, only Portfolio C has carbon emissions • Portfolio B is the only portfolio that does not emit NOx in 2035, because it retires all its thermal assets in 2034 2 O C l a u n n A 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 Annual and Cumulative CO2 Emissions (Million Tons) 15.42 7.91 7.23 2.31 18 16 14 12 10 8 6 4 2 0 2 O C e v i t a u m u C l Zero carbon emissions can be achieved either by converting gas-burning plants to hydrogen, or by retiring & replacing them with local solar and storage. 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 A B C D Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 55 Portfolio Reliability • Reliability improves over time, with all portfolios far more reliable in 2035 than in 2025 as more local resources are built to serve high load periods. All are below a typical 2.4-hour threshold used in reliability analysis. • Portfolios start with ~70 hours at risk of load loss, decreasing to under one hour by 2035 • Extra local, firm peaker capacity enables Portfolio D to handle extreme load events and contingencies • Reliant solely on transmission, local solar, & local storage for energy and capacity in 2035, Portfolio B has the highest risk of load loss 100 80 60 40 20 0 Annual Hours at Risk of Load Loss 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2.4-hour threshold A B C D 2035 Hours at Risk of Load Loss P5 MEAN P95 Portfolio A Portfolio B Portfolio C Portfolio D 0.16 0.28 0.63 0 0.63 4.76 0.14 0.44 0.89 0.15 0.25 0.40 Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 56 Conclusion 57 Key Takeaways • Using renewables and storage instead of peakers is very expensive: In Portfolio B, costs nearly double and 28,000 acres in Austin are required to site solar and storage (10% of Austin Energy's service area). However, B is the only Portfolio with no NOx emissions in 2035. • There is increasing marginal cost to remove emissions: Reducing cumulative carbon emissions from 15 to 7 Million tons increases total net costs by $1 Billion. Further reducing emissions from 7 to 2 million tons increases costs by $6 Billion. • All Portfolios are reliable by 2035: Portfolio D adds 525 MW more local peakers than A does. This improves reliability and increases emissions by about 10% each and has a negligible cost impact. 15.42 13.37 7.08 7.19 7.23 5.92 7.91 18 16 14 12 10 8 6 4 2 0 Cumulative Net Cost ($B) Cumulative CO2 Emissions 2.31 (Million Tons) A B C D 0.28 0.63 0.44 0.25 2035 Hours at Risk of Load Loss Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 58 Moving Forward... There is more than one way to get to zero supply stack emissions by 2035 In finding a balance between cost and emissions over the next decade, there is increasing marginal cost to remove emissions To achieve zero carbon and local reliability, limiting which dispatchable technologies can be chosen has the potential to greatly increase cost and siting needs. Building local peakers increases reliability with a negligible increase in cost and a marginal increase in emissions. Copyright Ascend Analytics. Do not duplicate or distribute without written permission from Ascend Analytics. 59  Ben Anderson Manager of Resource Planning banderson@ascendanalytics.com 1877 Broadway Street | Suite 706 | Boulder, CO 80302 | (303) 415 1400 General Reminders • 17 portfolios studied to date • 13 Austin Energy & EUC-defined portfolios • 4 Ascend Analytics (software-optimized) portfolios • Several portfolios included for reference only • Edge cases, purposefully defined to help understand the boundaries • Slides show raw data for comparison across portfolios • We're not drawing conclusions Portfolio Evaluation • With these portfolios, tradeoffs are significant • With the information gained from these portfolios, we will need to refine • Next step: Ask "what if?" and refine portfolios by mixing different technologies, seeking a more acceptable set of tradeoffs PORTFOLIO A PORTFOLIO B PORTFOLIO C PORTFOLIO D PORTFOLIO E PORTFOLIO F Refine Portfolios 61 Discussion & Collaboration ! What did you observe? What surprised you? What questions do you have? If you could change something and then re-run the model, what would it be? 62 EUC Office Hours • Tuesday, Oct. 1 1 p.m. – 3 p.m. • Wednesday, Oct. 2 11 a.m. – 1 p.m. • Thursday, Oct. 3 2:30 p.m. – 4 p.m. • Friday, Oct. 4 10 a.m. – 12 p.m. If none of the above times work, please let us know so we can find a time to collaborate. Office Hours Objectives: Office Hours Objectives: • Review detailed results • Review detailed results • Ask questions • Ask questions • Determine takeaways • Determine takeaways • Refine portfolios • Refine portfolios By Friday, Oct. 4 – Define a small set of portfolios for further analysis 63 ©Austin Energy. All rights reserved. Austin Energy and the Austin Energy logo and combinations thereof are trademarks of Austin Energy, the electric department of the City of Austin, Texas. Other names are for informational purposes only and may be trademarks of their respective owners.