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Optimizing power generation in the presence of micro-grids

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  • van Ackooij, Wim
  • De Boeck, Jérôme
  • Detienne, Boris
  • Pan, Stefania
  • Poss, Michael

Abstract

In this paper we consider energy management optimization problems in a future wherein an interaction with micro-grids has to be accounted for. We will model this interaction through a set of contracts between the generation companies owning centralized assets and the micro-grids. We will formulate a general stylized model that can, in principle, account for a variety of management questions such as unit-commitment. The resulting model, a bilevel stochastic mixed integer program will be numerically tackled through a novel preprocessing procedure. As a result the solution for the bilevel (or single leader multiple follower) problem will be neither “optimistic” nor “pessimistic”. We will numerically evaluate the difference of the resulting solution with the “optimistic” solution. We will also demonstrate the efficiency and potential of our methodology on a set of numerical instances.

Suggested Citation

  • van Ackooij, Wim & De Boeck, Jérôme & Detienne, Boris & Pan, Stefania & Poss, Michael, 2018. "Optimizing power generation in the presence of micro-grids," European Journal of Operational Research, Elsevier, vol. 271(2), pages 450-461.
  • Handle: RePEc:eee:ejores:v:271:y:2018:i:2:p:450-461
    DOI: 10.1016/j.ejor.2018.05.042
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    References listed on IDEAS

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    6. James T. Moore & Jonathan F. Bard, 1990. "The Mixed Integer Linear Bilevel Programming Problem," Operations Research, INFORMS, vol. 38(5), pages 911-921, October.
    7. W. Ackooij & I. Danti Lopez & A. Frangioni & F. Lacalandra & M. Tahanan, 2018. "Large-scale unit commitment under uncertainty: an updated literature survey," Annals of Operations Research, Springer, vol. 271(1), pages 11-85, December.
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    Cited by:

    1. Chai, Shanglei & Zhang, Xichun & Abedin, Mohammad Zoynul & Chen, Huizheng & Lucey, Brian & Hajek, Petr, 2023. "An optimized GRT model with blockchain digital smart contracts for power generation enterprises," Energy Economics, Elsevier, vol. 128(C).
    2. Jicheng Liu & Fangqiu Xu & Shuaishuai Lin & Hua Cai & Suli Yan, 2018. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization," Energies, MDPI, vol. 11(12), pages 1-22, November.
    3. Yıldıran, Uğur, 2023. "Robust multi-stage economic dispatch with renewable generation and storage," European Journal of Operational Research, Elsevier, vol. 309(2), pages 890-909.
    4. Abdelfettah Kerboua & Fouad Boukli-Hacene & Khaldoon A Mourad, 2020. "Particle Swarm Optimization for Micro-Grid Power Management and Load Scheduling," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 71-80.
    5. Aussel, Didier & Brotcorne, Luce & Lepaul, Sébastien & von Niederhäusern, Léonard, 2020. "A trilevel model for best response in energy demand-side management," European Journal of Operational Research, Elsevier, vol. 281(2), pages 299-315.
    6. López-Ramos, Francisco & Nasini, Stefano & Sayed, Mohamed H., 2020. "An integrated planning model in centralized power systems," European Journal of Operational Research, Elsevier, vol. 287(1), pages 361-377.
    7. Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).

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