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Bilevel optimization to deal with demand response in power grids: models, methods and challenges

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  • Carlos Henggeler Antunes

    (University of Coimbra)

  • Maria João Alves

    (University of Coimbra)

  • Billur Ecer

    (Ankara Yildirim Beyazit University)

Abstract

This paper presents a review of selected models, methods, and challenges associated with the use of bilevel optimization in problems that involve consumers’ demand response arising in the power sector. The main formulations and concepts of bilevel optimization are presented. The importance of demand response as a “dispatchable” resource in the evolution of power networks to smart grids is emphasized. The hierarchical nature of the interaction between decision-makers controlling different sets of variables in several problems involving demand response is highlighted, which establishes bilevel optimization as an adequate approach to decision support. The main concepts and solution approaches to those problems are underlined, in the context of the theoretical, methodological, and computational issues associated with bilevel optimization.

Suggested Citation

  • Carlos Henggeler Antunes & Maria João Alves & Billur Ecer, 2020. "Bilevel optimization to deal with demand response in power grids: models, methods and challenges," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 814-842, October.
    • Handle: RePEc:spr:topjnl:v:28:y:2020:i:3:d:10.1007_s11750-020-00573-y
    DOI: 10.1007/s11750-020-00573-y
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    References listed on IDEAS

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    Cited by:

    1. Beraldi, Patrizia & Khodaparasti, Sara, 2023. "Designing electricity tariffs in the retail market: A stochastic bi-level approach," International Journal of Production Economics, Elsevier, vol. 257(C).
    2. Arega Getaneh Abate & Rosana Riccardi & Carlos Ruiz, 2021. "Dynamic tariffs-based demand response in retail electricity market under uncertainty," Papers 2105.03405, arXiv.org, revised Feb 2024.
    3. Henggeler Antunes, Carlos & Alves, Maria João & Soares, Inês, 2022. "A comprehensive and modular set of appliance operation MILP models for demand response optimization," Applied Energy, Elsevier, vol. 320(C).

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