1. Wind Power Producers’ Costs And Associated Market Regulations: The Source of Wind Power Producers’ Market Power Yang Yu Stanford university 33rd USAEE/IAEE North Conference, Pittsburgh, PA

2. Market Power and Wind Power  Research on market power includes – Examining strategies to exercise market power (Borenstein,eta 2002) – Measuring market power (Wolak,2003)  Wind power producers (WPPs) are considered as price takers because – Zero marginal fuel costs – Decentralized market structure  Research Questions – Do WPPs have market power? – What are WPP’s strategies? Hourly Wind Penetration > 50% Germany, 2015-7-25 12pm-2pm

3. Revealed Wind For 2am WPPs’ Bidding Rule and Uncertain Nature Day-ahead (DA) MarketReal-time (RT) Market Demand and Wind-Energy DistributionsRevealed Wind-Energy Level Conventional Generator WPP Supply (MWhs) Price ($/MWhs) Supply (MWhs) Commitment For 2am Wind Energy Supply (MWhs) 200 MWh If WPP over commits Hourly BiddingUncertain Nature WPP buys 100 MWh Hour

4. A Stochastic Two-Hour Model Day-ahead (DA) MarketReal-time (RT) Market Demands and Wind-Energy Distributions in Two Hours Exact Wind-Energy Level Wind RT (h) in Each Hour If Wind RT (h) < Wind DA (h), the WPP buys electricity WPP’s Benefit: P DA (h) × Wind DA (h) WPP’s Opportunity Cost: P RT (h) × (Wind DA (h) -Wind RT (h)) + Hourly Incremental Cost Minimization P DA (h) = MC gas (Q gas ) = MC coal (Q coal ) + λ(h) Coal Plant: linear marginal cost MC coal (Q coal ) max-ramp rate: r Gas Plant: linear marginal cost MC coal (Q coal ) WPP: Hourly Commitment Wind DA (h)

5. Price Sensitivity to WPP’s Commitment  Residual inverse demand (RID) curve (McRae&Wolak,2009) Wind DA (2) Q coal (2) Q gas (2) Wind DA (2) Q coal (2) Q gas (2) P DA (2) =MC gas (Q gas ) =MC coal (Q coal ) + λ(h) Demand(MWhs) Hour 2 Tipping Point DA Price Wind Commitment The WPP’s RID in Hour 2 When the Net Load Is Ramping Up

6. WPP’s Marginal Cost Is Non-Zero Day-ahead (DA) MarketReal-time (RT) Market  Theorem : the WPP’s marginal cost in the DA market is  MC wind is non-zero – WPPs do not compete with zero-cost generators,  MC wind varies by wind-energy distributions – WPPs does not necessarily compete with each other. P DA (h) × Wind DA (h) – E[P RT (h) × (Wind DA (h) -Wind RT (h)) + ]

7. The WPP’s Ability to Manipulate Price  WPP has ability to manipulate the price when e < 0 Wind Commitment DA Price MC wind Wind DA * Wind DA ’ Wind DA *: market-power commitment ; Wind DA ’: price-taker commitment Tipping Point e: Elasticity of RID curve between [Wind DA *, Wind DA ’]

8. WPPs’ Market Power in ERCOT in 2012  Data ： – Demand and wind energy in 2012: ERCOT – Technical feature of conventional generators: E-Grid  Scenario: WPPs aggregately bid in the market  904 out of 8783 hours, WPPs have market power (e < 0) – Average of e: 2%. Max of e: 9%. Wind Energy PenetrationProbability that WPPs Have Market Power WPP’s market power is a big problem in a future grid Aggregated bidding need to be limited Low penetration ≠ No market power WPP’s market power is a big problem in a future grid Aggregated bidding need to be limited Low penetration ≠ No market power

9. Hours When WPPs Have Market Power Histogram of WPPs’ Hourly Marginal Costs in ERCOT ERCOT’s Aggregate Supply Curve of fossil-fuel Generators Coal Gas Oil

10. DA-Bidding Rule and WPP’s Non-zero Marginal Cost Take Advantage of Coal Plant’s Ramping Limit Hourly-Commitment Bidding Rule WPP Can and Will Raise Price by Increasing Commitment

11. Generate More to Increase Neighboring-hour Price Lemma: Given Wind DA (2), the increase of Wind DA (1) raises P DA (2) Hour 2 Wind Commitment DA Price Wind DA (2) Wind DA (1) Demand(1) Hour 1 Wind DA (2) Hour 2 Wind DA (1) Hour 1 Wind DA (2) Δ > r Δ Δ Demand(2) Demand(1) Coal plant generates less in hour 2 Price increases in hour 2 Coal plant generates less in hour 2 Price increases in hour 2 Q coal (q) Q coal (2) Hour 2 Q coal (q)

12. WPP’s Strategy to Utilize Ramp Constraints  Theorem: Because θ > 0, WPP increases Wind DA (1) to raise P DA (2) Hour 2 Wind Commitment DA Price Wind DA (2)  The WPP’s optimal strategy in hour 1 satisfy ： θ > 0

13. Insights and Suggestions  WPP’s abilities to exercise market power are unique because they come from – Current regulations – Wind power generator’s fast-ramping feature  Reexamine current mechanisms to mitigate market power – The use of long-term contract – Restriction on WPPs’ aggregate bidding (Bitar et.al 2012)  New indices are needed to hourly monitor WPPs’ abilities to exercise their market power

14. Summary  A Stochastic-two-hour game model is developed to analyze WPP’s market power – WPPs’ marginal cost is non-zero and change by hours Compete with non-zero-cost generators Not necessarily compete with each other  WPPs have ability to raise price by – reducing generation commitments Even in low-penetration case – increasing generation commitments in neighboring hours Generate more and raise price higher

15. Thank you.  Questions?  yangyu1@stanford.edu

16. Conditions Under Which WPP Has Market Power  A steep slope of each piece Competitors have fast-increasing supply curve  A high value of the tipping point Net-demand is fast increasing Competitors’ ramp rates are limited Wind Commitment DA Price Wind DA * Wind DA ’ Tipping Point

17. Reference  [1] Ito, Koichiro, and Mar Reguant. Sequential Markets, Market Power and Arbitrage. No. w20782. National Bureau of Economic Research, 2014.  [2] Borenstein, S., Bushnell, J. B., Wolak, F. A., 2002. Measuring market inefficiencies in california’s restructured wholesale electricity market. AER 92 (5).  [3] McRae, Shaun D., and Frank A. Wolak. "How do firms exercise unilateral market power? Evidence from a bid-based wholesale electricity market." (2009).  [4] F. A. Wolak, “Measuring unilateral market power in wholesale electricity markets: the california market, 1998-2000,” The American economic review, vol. 93, no. 2, pp. 425–430, 2003.  [5] E. Y. Bitar, R. Rajagopal, P. P. Khargonekar, K. Poolla, and P. Varaiya, “Bringing wind energy to market,” Power Systems, IEEE Transactions on, 2012.

18. Back Up Slides

19. DA-Bidding Rule and WPP’s Non-zero Marginal Cost Wind-Energy Uncertinaty Possible Payment for Wind Shortfall Marginal Cost ≠ 0 WPP Can Raise Price by Reducing Commitment

20. WPPs Have Market Power Even When the Penetration Is Small  In over 900 hours of 2012, the WPPs in the ERCOT market have ability to manipulate the price if they aggregately bid – Average penetration: 17.8% – In 78 hours, the market share of WPPs is less than 5% – In 6 hours when the market share < 1%, WPPs have market power – In more than 200 hours when the market share > 30%, WPPs do not have market power Histogram of WPPs’ Hourly Marginal Costs in ERCOT ERCOT’s Aggregate Supply Curve of Conventional Generators

21. Background  Do WPPs have market powers? – Single Company separate bid – Aggregate bidding  What is a WPP’s optimal strategy when it exercises its market power Increasing Wind- Energy Penetration Geographic Imbalance of Wind Energy Generation Single Company’s High Market Share in a Particular Hour Needs of Aggregate Bidding of Wind Power Producers (WPPs) Forecast Error Decrease by Aggregate Bidding Research Questions

22. DA Price Changes With the WPP’s Commitment Reduce Commitment in a Hour WPP System Operator Coal and Gas Generation  Binding Coal’s Ramping Limit Change DA Prices in this and other hours P DA (Wind Commitment):Residual Inverse Demand (RID) Curve to the WPP How DA price responds to the change of WPP’s  Lemma: The DA price satisfy the following condition DA Price =MC gas (G gas ) =MC coal (G coal ) + λ(t)  λ is the dual variable of the Ramping Constraint in hour t

23. The RID curve is a Piece-wise Function  Theorem(DA price): The DA market price is a function of the WPP’s Commitment: DA Price = MC coal (Demand – G gas – Wind Commitment) + λ The WPP’s RID in Hour 2 When the Net Load Is Ramping Up Tipping Point Wind Commitment DA Price Price Increases Slow When the Ramping Constraint is lessened Price Increases Fast When the Ramping Constraint is Binding Price Sensitivity to the WPP’s commitment

24. Factors Determining Price Sensitivity Tipping Point Wind Commitment DA Price Marginal Costs of Competitors Fast Increase Coal Plant’s Ramp Rate Is Limited WPP’s Commitment in Hour 1 Is Hihg Load Difference is Large The WPP’s RID in Hour 2 When the Net Load Is Ramping Up  The Price is sensitive when Value of Tipping Point Is Large

25. Future Grid: More Risks of Wind Power’s Market Power Wind Energy’s Penetration Percentage of Hours When WPP Has Ability to Manipulate the Price  When the hourly wind penetration increases, the probability that WPPs have ability to manipulate price increases  In many hours, WPPs do not have market power when they aggregate

26. Background  Increasing concern about the market power of a single wind power producer (WPP) – Fast growing of wind energy’s penetration – Geographic unbalance of hourly wind energy’s generation  Debate about whether WPPs could be allowed to aggregated make bid in a electricity market – Pros: reducing forecast errors [1] – Cons: concerns of the market power of aggregated WPPs