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Demand shifting bids in energy auction with non-convexities and transmission constraints

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  • Zoltowska, Izabela

Abstract

The major objective of this paper was to propose clearing and pricing models suitable for demand shifting bids in the efficient, but non-convex pool-based auction. Complex generators' offers bring non-convexities into the efficient auctions due to e.g. start-up costs and times. This paper focused on the responsive demands, introducing simple, yet adequate linear constraints into a multi-period bid/offer-based optimal power flow (OPF DC) model. As the standard locational marginal prices (LMPs) may not support the auction outcomes due to non-convexities, uplifts are needed to reduce generators' loss. Previous work has developed a minimum-uplift pricing model that directly optimizes prices, so that uplifts arising from generators' profit-suboptimality and simple, elastic demands' benefit-suboptimality are minimized. This work extended the mixed integer linear programming (MILP) formulation of the previous model to incorporate new linear constraints defining benefit-suboptimality of demand shifting bids. Furthermore, the transmission constrained market was attempted. As a result, the buyers were protected against over-curtailment; moreover, prices complemented with minimum uplifts were fair for both generators and demands. The models were validated on the literature-based cases, including IEEE RTS 24-node 24-hour system.

Suggested Citation

  • Zoltowska, Izabela, 2016. "Demand shifting bids in energy auction with non-convexities and transmission constraints," Energy Economics, Elsevier, vol. 53(C), pages 17-27.
    • Handle: RePEc:eee:eneeco:v:53:y:2016:i:c:p:17-27
    DOI: 10.1016/j.eneco.2015.05.016
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    References listed on IDEAS

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    1. Garci'a-Bertrand, Raquel & Conejo, Antonio J. & Gabriel, Steven, 2006. "Electricity market near-equilibrium under locational marginal pricing and minimum profit conditions," European Journal of Operational Research, Elsevier, vol. 174(1), pages 457-479, October.
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    3. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    4. O'Neill, Richard P. & Sotkiewicz, Paul M. & Hobbs, Benjamin F. & Rothkopf, Michael H. & Stewart, William R., 2005. "Efficient market-clearing prices in markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 164(1), pages 269-285, July.
    5. Toczylowski, Eugeniusz & Zoltowska, Izabela, 2009. "A new pricing scheme for a multi-period pool-based electricity auction," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1051-1062, September.
    6. Izabela Żółtowska & Eugeniusz Toczyłowski, 2009. "A compensation-based pricing scheme in markets with non-convexities," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(4), pages 125-140.
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    Cited by:

    1. Izabela Zoltowska & Jeremy Lin, 2021. "Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids," Energies, MDPI, vol. 14(16), pages 1-18, August.
    2. Lejeune, Miguel A. & Dehghanian, Payman & Ma, Wenbo, 2024. "Profit-based unit commitment models with price-responsive decision-dependent uncertainty," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1052-1064.
    3. Martin Bichler & Johannes Knörr & Felipe Maldonado, 2023. "Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response," Information Systems Research, INFORMS, vol. 34(2), pages 652-675, June.
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    6. Bichler, Martin & Knörr, Johannes, 2023. "Getting prices right on electricity spot markets: On the economic impact of advanced power flow models," Energy Economics, Elsevier, vol. 126(C).

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    More about this item

    Keywords

    Double auction; Unit commitment; Energy pricing; Minimum uplift; Individual maximum profits;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D51 - Microeconomics - - General Equilibrium and Disequilibrium - - - Exchange and Production Economies
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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