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Journal of Regulatory Economics

, Volume 21, Issue 3, pp 247–288 | Cite as

Rational Buyer Meets Rational Seller: Reserves Market Equilibria under Alternative Auction Designs

  • Rajnish Kamat
  • Shmuel S. Oren
Article

Abstract

We examine efficiency properties and incentive compatibility of alternative auction formats that an electricity network system operator may use for the procurement of ancillary services required for real-time operations. We model the procurement auction as a hierarchical multiproduct auction, and study several designs such as a uniform price auction minimizing revealed “social” cost, a uniform price auction minimizing the system operator's cost and a pay as bid auction minimizing revealed “social” cost. We take into account that rational bidders will respond to any market design so as to maximize their expected benefit from participating in that market. Under the assumptions of our model, we show that the uniform price auction minimizing revealed “social” cost is the only one that guarantees productive efficiency. We also find that expected revenue (payment in our case) equivalence between pay as bid and uniform price auctions does not extend to the hierarchical products case and the ranking of these auctions is ambiguous and depends on the data. For the procurement auction minimizing the system operator's cost, we show that misrepresentation of capability may result in capacity shortages if there are capacity constraints. For the case where only higher capability resources are constrained, this will result in random price spikes decreasing in frequency with the price cap (this is the amount paid to capacity in demand states with shortages). When lower type resources are capacity constrained as well, price spikes will be seen for both type of resources. Such artificial shortages result in reduced reliability in real-time operations.

Keywords

Incentive Compatibility Ancillary Service Market Design Auction Format Procurement Auction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Rajnish Kamat
    • 1
  • Shmuel S. Oren
    • 2
  1. 1.Department of Industrial Engineering and Operations ResearchUniversity of California at BerkeleyBerkeleyU.S.A.
  2. 2.Department of Industrial Engineering and Operations ResearchUniversity of California at BerkeleyBerkeleyU.S.A.

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