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Optimization-based modelling and game-theoretic framework for techno-economic analysis of demand-side flexibility: A real case study

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  • Sayfutdinov, Timur
  • Patsios, Charalampos
  • Greenwood, David
  • Peker, Meltem
  • Sarantakos, Ilias

Abstract

This paper proposes a two-step framework for techno-economic analysis of a demand-side flexibility service in distribution networks. Step one applies optimization-based modelling to propose a generic problem formulation which determines the offer curve, in terms of available flexible capacity and its marginal cost, for flexible distribution-connected assets. These offer curves form an input to the second step, which uses a multi-agent iterative game framework to determine the benefits of demand-side flexibility for the Distribution System Operator (DSO) and the service providers. The combined two-step framework simultaneously accounts for the objectives of each flexibility provider, technical constraints of flexible assets, customer preferences, market clearing mechanisms, and strategic bidding by service providers, omission of any of which can lead to erroneous results. The proposed two-step framework has been applied to a real case study in the North East of England to examine four market mechanisms and three bidding strategies. The results showed that among all considered market mechanisms, flexibility markets that operate under discriminatory pricing, such as pay-as-bid and Dutch reverse auctions, are prone to manipulations, especially in the lack of competition. In contrast, uniform pricing pay-as-cleared auction provides limited opportunities for manipulation even when competition is low.

Suggested Citation

  • Sayfutdinov, Timur & Patsios, Charalampos & Greenwood, David & Peker, Meltem & Sarantakos, Ilias, 2022. "Optimization-based modelling and game-theoretic framework for techno-economic analysis of demand-side flexibility: A real case study," Applied Energy, Elsevier, vol. 321(C).
  • Handle: RePEc:eee:appene:v:321:y:2022:i:c:s0306261922007139
    DOI: 10.1016/j.apenergy.2022.119370
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    References listed on IDEAS

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    1. Philippe Gillen & Alexander Rasch & Achim Wambach & Peter Werner, 2016. "Bid pooling in reverse multi-unit Dutch auctions: an experimental investigation," Theory and Decision, Springer, vol. 81(4), pages 511-534, November.
    2. Madzharov, D. & Delarue, E. & D'haeseleer, W., 2014. "Integrating electric vehicles as flexible load in unit commitment modeling," Energy, Elsevier, vol. 65(C), pages 285-294.
    3. Haji Hosseinloo, Ashkan & Ryzhov, Alexander & Bischi, Aldo & Ouerdane, Henni & Turitsyn, Konstantin & Dahleh, Munther A., 2020. "Data-driven control of micro-climate in buildings: An event-triggered reinforcement learning approach," Applied Energy, Elsevier, vol. 277(C).
    4. Poplavskaya, Ksenia & Lago, Jesus & de Vries, Laurens, 2020. "Effect of market design on strategic bidding behavior: Model-based analysis of European electricity balancing markets," Applied Energy, Elsevier, vol. 270(C).
    5. Reis, Inês F.G. & Gonçalves, Ivo & Lopes, Marta A.R. & Antunes, Carlos Henggeler, 2020. "A multi-agent system approach to exploit demand-side flexibility in an energy community," Utilities Policy, Elsevier, vol. 67(C).
    6. Sayfutdinov, Timur & Vorobev, Petr, 2022. "Optimal utilization strategy of the LiFePO4 battery storage," Applied Energy, Elsevier, vol. 316(C).
    7. Michael H. Rothkopf, 2007. "Thirteen Reasons Why the Vickrey-Clarke-Groves Process Is Not Practical," Operations Research, INFORMS, vol. 55(2), pages 191-197, April.
    8. Zhanle Wang & Raman Paranjape & Zhikun Chen & Kai Zeng, 2019. "Multi-Agent Optimization for Residential Demand Response under Real-Time Pricing," Energies, MDPI, vol. 12(15), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

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