Demand Curve Shape. Preliminary Modeling Results and Scoping Questions. Demand Curve Working Group P R E P A R E D F O R P R E P A R E D B Y

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1 Demand Curve Shape Preliminary Modeling Results and Scoping Questions P R E P A R E D F O R Demand Curve Working Group P R E P A R E D B Y Kathleen Spees Judy Chang Johannes Pfeifenberger David Luke Oates Peter Cahill Elliott Metzler O c t o b e r 1 0, D r a f t M a t e r i a l s f o r D i s c u s s i o n Copyright 2017 The Brattle Group, Inc.

2 Agenda Overview Modeling Approach Supply Curve Concepts Initial Results Next Steps 1 brattle.com

3 Overview The AESO has asked us to provide analytical support to the Working Group as you develop a capacity market demand curve Our tasks are to: Assist the Working Group to understand the potential performance of demand curves under consideration, drawing on experience from other markets and analysis of Alberta s unique situation (i.e. small market, coal retirements, transition from energy-only, possible seasonal construct) Provide modeling support to assess potential price and quantity volatility with each demand curve under long-run equilibrium conditions (approach for assessing questions on near-term, transitional conditions is being reviewed by AESO) Identify open questions from the group and answer them in upcoming meetings (see next steps for open questions gathered to date) We kick off that discussion today with a preliminary analysis of how other markets curves would perform in Alberta, a sketch of curves tuned to Alberta s market size, and discussion of the supply curve 2 brattle.com

4 Overview Concept: Tuned Demand Curves Preliminary analysis indicates that Alberta s small market may require a proportionally wider demand curve to mitigate expected price and net supply variability Standard deviation in clearing prices ranges between 25% and 45% of Net CONE Minimum Acceptable: 800 MWh/year EUE (Preliminary Working Assumption) Tuned, Cap at 2 Net CONE Target: 100 MWh/year EUE (Preliminary Working Assumption) Tuned, Cap at 1.7 Net CONE Tuned, Cap at 1.5 Net CONE Tuned Demand Curves Capacity markets will have year-to-year variability in supply and demand Other markets developed demand curves tuned to achieve the reliability requirement on average (though reliability varies from year to year) Applying that approach to Alberta, curves such as these would achieve 100 MWh/year EUE ~3,000-4,000 MW Range % of Reliability Requirement Reserve Margin (% UCAP) UCAP MW Preliminary Working Assumptions 3 brattle.com

5 Agenda Overview Modeling Approach Supply Curve Concepts Initial Results Next Steps 4 brattle.com

6 Modeling Approach Recap: Overview of Modeling Approach Primary Model Results Estimate average, range, and distribution of capacity market outcomes Price, quantity, and reliability Across annual or summer/winter auctions Summarize results realized with different demand curve shapes Approach Incorporate annual or seasonal supply and demand curves Clear supply and demand to calculate prices and quantities in the auction Simulate a distribution of outcomes using a Monte Carlo analysis of realistic shocks to supply, demand, and imports Average price over all draws must equal Net CONE, consistent with a market that supports entry at long-run marginal cost Supply and Demand Shocks (Illustrative) Range of Price Outcomes Demand Shocks Supply Shocks Range of Quantity Outcomes Net CONE 5 brattle.com

7 Modeling Approach Supply Modeling Supply curves consist of three components Shape Blocks Supply offers at prices above zero Shape based on historical PJM offer curves Scaled to total MW offers, which vary based on annual vs. summer/winter auction type Independent of demand curve shape Supply Curve Components (Illustrative) Shock Block Zero-priced supply block Quantity varies with each draw to generate shocks to the supply curve Represents expected year-to-year variability Shape Block Smart Block Zero-priced supply block Smart Block Shock Block Quantity adjusted such that the average price across all draws equals Net CONE Quantity is constant across draws, but may be slightly different across demand curves 6 brattle.com

8 Modeling Approach Demand and Reliability Modeling Demand Curves Arbitrary number of price-quantity pairs Quantities are relative to the reliability requirement Prices expressed as % of Net CONE Reliability Simulation reliability results are evaluated with respect to expected unserved energy (EUE) and a working assumption for reliability target EUE curve and target will be updated as new information becomes available Using quantity outputs, the EUE is tabulated over all simulation draws to estimate weighted-average reliability outcomes Demand Curve and Reliability (Illustrative) EUE Curve Minimum Acceptable: 800 MWh/year EUE (Preliminary Working Assumption) Target: 100 MWh/year EUE (Preliminary Working Assumption) Preliminary Working Assumption 7 brattle.com

9 Modeling Approach Preliminary Model Inputs Preliminary model inputs consistent with 2022 delivery year Based on best available information at this time (see appendix for detail) AESO and Brattle staff are continuing to refine working assumptions Expect changes to results as we refine input assumptions Inputs for Annual Auction Mode Preliminary Working Assumptions 8 brattle.com

10 Agenda Overview Modeling Approach Supply Curve Concepts Initial Results Next Steps 9 brattle.com

11 Supply Curve How Do Sellers Offer in Other Markets? In other forward capacity markets, approximately 70-85% of suppliers offer at a price of zero. Prices are set by the subset of above-zero offers ISO-NE and PJM Three-Year Forward Markets PJM Three-Year Forward and MISO Non-Forward Market Supply Curves Affected by the Mercury & Air Toxics Standard Many Coal Plants Faced Retire-or-Retrofit Decision at Once ISO New England PJM Range of Clearing Prices 2015/16-20/21 Clearing More Than 25,000 MW of New Generation Sources: Pfeifenberger et al. Third Triennial Review of PJM s Variable Resource Requirement Curve (2014) Testimony of Dr. Samuel A. Newell and Dr. Kathleen Spees on Behalf of ISO New England Inc. Regarding a Forward Capacity Market Demand Curve (2014) Testimony of Dr. Samuel A. Newell, Dr. Kathleen Spees, and Dr. David Luke Oates on Behalf of Midcontinent Independent System Operator (MISO). 10 brattle.com

12 Supply Curve What Drives the Offer Prices? Offer Price* = Going-Forward Fixed Costs Expected E&AS Net Revenue In a uniform price auction, the competitive offer price is at the minimum payment needed to break even for operating one more year. Over the lifecycle of a typical plant that translates to offers at: First Delivery Year: Offer at above-zero prices, consistent with investment costs minus expected net E&AS revenue (i.e. at Net CONE) Years 2+: Offer near zero. Energy market net revenues exceed goingforward fixed costs to stay in operation (plant will stay online even without capacity payments). The majority of plants fall into this category Aging Plant Needing Refurbishment: Offer at above-zero prices. Will retire or mothball if capacity price is too low to recover re-investment costs Notes: *Many other complexities affect offer prices, including opportunity costs, penalty and obligation costs under the capacity market, and the expected trajectory of energy and capacity prices in years 2+. This simplified discussion covers only the largest drivers of offer prices for traditional thermal generating resources. 11 brattle.com

13 Agenda Overview Modeling Approach Supply Curve Concepts Initial Results Next Steps 12 brattle.com

14 Initial Results Tested Demand Curves Tested several demand curves for performance if translated to Alberta s context. Compared: Vertical curve PJM, ISO-NE, and NYISO curves Tuned straight-line curves with price caps 1.5 to 2 Net CONE, and foot point adjusted until reliability is at the target NYISO Minimum Acceptable: 800 MWh/year EUE (Preliminary Working Assumption) Demand Curves Tested Target: 100 MWh/year EUE (Preliminary Working Assumption) PJM Tuned, Cap at 2 Net CONE Tuned, Cap at 1.7 Net CONE Tuned, Cap at 1.5 Net CONE ISO-NE Preliminary Working Assumptions % of Reliability Requirement Reserve Margin (% UCAP) UCAP MW 13 brattle.com

15 Initial Results Histogram Results (PJM Curve) When applied to AESO, PJM s demand curve results in a significant number of auctions with prices at the cap and low reliability Prices Prices often at the administrative cap, high price volatility Minimum Acceptable: 800 MWh/year EUE (Preliminary Working Assumption) Quantities Target: 100 MWh/year EUE (Preliminary Working Assumption) Quantities often below the minimum acceptable threshold 14 brattle.com

16 Initial Results Preliminary Results: Demand Curve Performance Initial results indicate that Alberta may need a proportionally wider/flatter demand curve than those used in other markets to mitigate price volatility and reliability in the smaller market Model Simulation Results for Selected Demand Curves Average prices equal Net CONE with all curves Vertical curve produces high price volatility The existing RTO and vertical curves support reliability far below the target The tuned curves achieve target reliability at 100 MWh/year EUE Existing RTO and vertical curves fall short of the requirement about 1/3 to 1/2 of the time 15 brattle.com

17 Agenda Overview Modeling Approach Supply Curve Concepts Initial Results Next Steps 16 brattle.com

18 Next Steps Questions from the Working Group Brattle and AESO are seeking input from the workgroup to guide further demand curves or sensitivities to evaluate. Building on discussion from the last meeting, potential questions include: How sensitive are tuned curves to supply/demand shocks, reliability requirement, and supply curve shapes? What s the equilibrium MW of supply compared to current, and how long would it take Alberta to reach equilibrium with each demand curve? What supply curve sensitivities make sense to test for the specific Alberta context (e.g. existing suppliers offer at 50% of Net CONE)? How should the Working Group think about the demand curve in the context of a seasonal auction? How should the demand curves reflect incremental reliability benefits and the value of lost load? Additional questions identified in this meeting or submitted offline 17 brattle.com

19 Next Steps Timing SAM Sept-Dec 2017 SAM Jan-Mar 2018 SAM Apr-Jun 2018 Scope Oct 4 Web/Phone Meeting Gather feedback from workgroup on scope Oct 10 In-Person Meeting (Today): Discuss preliminary analysis of potential demand curve shapes Review Alberta-specific considerations affecting price volatility and desirable curve width/parameters Expand on and complement introduction of demand curve concepts/principles by providing information on modeling approach, impacts of key parameters and principles, preliminary suggestions about the workable range of demand curve parameters Nov 1 Meeting: Develop materials in response to workgroup questions, requested sensitivity analysis, and requested demand curve alternatives. Provide 2-4 workable demand curve options for the workgroup to consider for SAM 3.0 Nov 15 Meeting: Respond to workgroup questions/input. Discuss demand curve selected for SAM 3.0, finalize principles Jan Meeting: Outline outstanding uncertainties/questions to be refined in SAM 4.0, primary interactions/uncertainties, gather stakeholder input on necessary refinements Feb or Mar Meeting: Answer outstanding questions, finalize demand curve parameters. Develop workgroup conclusion for SAM 4.0 demand curve parameters Make final adjustments to demand curve based on final AESO/workgroup input and conforming changes to other workgroups changes in SAM 4.0 April Meeting: Provide final presentation to the workgroup on selected demand curve and recommendations to be included in report. Last opportunity for stakeholder input/adjustments June Recommendations Report/Testimony: Prepare final recommendations report and deliver to workgroup/aeso. Document the defined objectives, principles, workgroup process, and dissention. Include final recommended Demand Curve. Submit report or testimony suitable for filing with governing body 18 brattle.com

20 Contact Information JUDY CHANG Principal and Director Boston, MA KATHLEEN SPEES Principal Boston, MA JOHANNES PFEIFENBERGER Principal Boston, MA DAVID LUKE OATES Associate Boston, MA The views expressed in this presentation are strictly those of the presenter(s) and do not necessarily state or reflect the views of The Brattle Group, Inc. 19 brattle.com

21 About The Brattle Group The Brattle Group provides consulting and expert testimony in economics, finance, and regulation to corporations, law firms, and governmental agencies worldwide. We combine in-depth industry experience and rigorous analyses to help clients answer complex economic and financial questions in litigation and regulation, develop strategies for changing markets, and make critical business decisions. Our services to the electric power industry include: Climate Change Policy and Planning Rate Design and Cost Allocation Cost of Capital Regulatory Strategy and Litigation Support Demand Forecasting Methodology Renewables Demand Response and Energy Efficiency Resource Planning Electricity Market Modeling Retail Access and Restructuring Energy Asset Valuation Risk Management Energy Contract Litigation Market-Based Rates Environmental Compliance Market Design and Competitive Analysis Fuel and Power Procurement Incentive Regulation Mergers and Acquisitions Transmission 20 brattle.com

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23 Appendix Model Input Details 22 brattle.com

24 Appendix Supply Shocks Applied to supply curves to capture real world variability in offered supply quantities Standard Deviation in Offered Supply Evaluated year-to-year variability in supply offers in similar-sized zones within PJM, MISO, and ISO-NE Standard deviations range 3%-7% Recommended mid-point of 5% Regions the Size of Alberta 23 brattle.com

25 Appendix Demand Shocks Applied to reliability requirement to account for expected variability in demand Historical Peak Load Forecast by Forecast Year Based on variability in AESO load forecasts 3 to 4 years out Supplemented based on variability in reliability requirements for other markets capacity zones the same size as Alberta Recommend 4% standard deviation as the midpoint, and 1.5%-7% sensitivity range Year-to-Year Variability in Demand in Comparably Sized Zones 24 brattle.com