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A non-cooperative multi-leader one-follower integrated generation maintenance scheduling problem under the risk of generation units’ disruption and variation in demands

Author

Listed:
  • Atefeh Hassanpour

    (K. N. Toosi University of Technology)

  • Emad Roghanian

    (K. N. Toosi University of Technology)

  • Mahdi Bashiri

    (Coventry University)

Abstract

The generation maintenance scheduling deals with a time sequence of preventive maintenance outages for a given set of generation units in an electricity market subject to power system restrictions. Incorporating a leader–follower structure in generation maintenance scheduling models is essential because of the inherent conflict between the interests of an independent system operator (ISO) and generation companies (GENCOs). The present paper proposes a new preventive maintenance scheduling model for generation companies facing the risk of involving generation units’ disruption and demand variations while ensuring the reliability of the power system. Each GENCO proposes the maintenance schedule of its generation units to the ISO in a non-cooperative manner intending to maximize its net profit. Then ISO reacts to the aggregated schedule according to the power system’s reliability index. Thus, a new formula is developed to consider all the interactions between the power system’s stakeholders. In this regard, a stochastic multi-leader one-follower approach is applied. The GENCOs are considered independent leaders at the upper-level and the ISO is considered a follower at the lower-level. Then an equivalent single-level counterpart model is presented for each leader. So, the whole problem is converted into multiple individual stochastic single-level models, and then the Nash Equilibrium concept is used to determine GENCO equilibrium strategies. The proposed methodology is evaluated using some modified IEEE reliability test systems. The numerical analysis confirms that the proposed model is more effective in cases with higher uncertainties. Moreover, the performed analysis demonstrated the importance of applying a bi-level approach to the problem. Finally, the superiority of the proposed approach compared to the existing one is confirmed.

Suggested Citation

  • Atefeh Hassanpour & Emad Roghanian & Mahdi Bashiri, 2024. "A non-cooperative multi-leader one-follower integrated generation maintenance scheduling problem under the risk of generation units’ disruption and variation in demands," Annals of Operations Research, Springer, vol. 336(3), pages 1591-1635, May.
  • Handle: RePEc:spr:annopr:v:336:y:2024:i:3:d:10.1007_s10479-023-05553-6
    DOI: 10.1007/s10479-023-05553-6
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    References listed on IDEAS

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    1. Tae-Woo Kim & Yenjae Chang & Dae-Wook Kim & Man-Keun Kim, 2020. "Preventive Maintenance and Forced Outages in Power Plants in Korea," Energies, MDPI, vol. 13(14), pages 1-12, July.
    2. Min, C.G. & Kim, M.K. & Park, J.K. & Yoon, Y.T., 2013. "Game-theory-based generation maintenance scheduling in electricity markets," Energy, Elsevier, vol. 55(C), pages 310-318.
    3. Froger, Aurélien & Gendreau, Michel & Mendoza, Jorge E. & Pinson, Éric & Rousseau, Louis-Martin, 2016. "Maintenance scheduling in the electricity industry: A literature review," European Journal of Operational Research, Elsevier, vol. 251(3), pages 695-706.
    4. Porter, Ryan & Nudelman, Eugene & Shoham, Yoav, 2008. "Simple search methods for finding a Nash equilibrium," Games and Economic Behavior, Elsevier, vol. 63(2), pages 642-662, July.
    5. Kralj, Branimir L. & Petrovic, Radivoj, 1988. "Optimal preventive maintenance scheduling of thermal generating units in power systems --A survey of problem formulations and solution methods," European Journal of Operational Research, Elsevier, vol. 35(1), pages 1-15, April.
    6. Thomas Bittar & Pierre Carpentier & Jean-Philippe Chancelier & Jérôme Lonchampt, 2022. "A decomposition method by interaction prediction for the optimization of maintenance scheduling," Annals of Operations Research, Springer, vol. 316(1), pages 229-267, September.
    7. Mazidi, Peyman & Tohidi, Yaser & Ramos, Andres & Sanz-Bobi, Miguel A., 2018. "Profit-maximization generation maintenance scheduling through bi-level programming," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1045-1057.
    8. James T. Moore & Jonathan F. Bard, 1990. "The Mixed Integer Linear Bilevel Programming Problem," Operations Research, INFORMS, vol. 38(5), pages 911-921, October.
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