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Uniform Pricing vs Pay as Bid in 100%-Renewables Electricity Markets: A Game-theoretical Analysis

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  • Dongwei Zhao
  • Audun Botterud
  • Marija Ilic

Abstract

This paper evaluates market equilibrium under different pricing mechanisms in a two-settlement 100%-renewables electricity market. Given general probability distributions of renewable energy, we establish game-theoretical models to analyze equilibrium bidding strategies, market prices, and profits under uniform pricing (UP) and pay-as-bid pricing (PAB). We prove that UP can incentivize suppliers to withhold bidding quantities and lead to price spikes. PAB can reduce the market price, but it may lead to a mixed-strategy price equilibrium. Then, we present a regulated uniform pricing scheme (RUP) based on suppliers' marginal costs that include penalty costs for real-time deviations. We show that RUP can achieve lower yet positive prices and profits compared with PAB in a duopoly market, which approximates the least-cost system outcome. Simulations with synthetic and real data find that under PAB and RUP, higher uncertainty of renewables and real-time shortage penalty prices can increase the market price by encouraging lower bidding quantities, thereby increasing suppliers' profits.

Suggested Citation

  • Dongwei Zhao & Audun Botterud & Marija Ilic, 2023. "Uniform Pricing vs Pay as Bid in 100%-Renewables Electricity Markets: A Game-theoretical Analysis," Papers 2305.12309, arXiv.org.
    • Handle: RePEc:arx:papers:2305.12309
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    References listed on IDEAS

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    1. Heim, Sven & Götz, Georg, 2021. "Do Pay-As-Bid Auctions Favor Collusion? Evidence from Germany's market for reserve power," Energy Policy, Elsevier, vol. 155(C).
    2. Barry L. Nelson, 2013. "Foundations and Methods of Stochastic Simulation," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-6160-9, April.
    3. Barry L. Nelson, 2013. "Simulation for Research," International Series in Operations Research & Management Science, in: Foundations and Methods of Stochastic Simulation, edition 127, chapter 0, pages 243-252, Springer.
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