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Profit-maximization generation maintenance scheduling through bi-level programming

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  • Mazidi, Peyman
  • Tohidi, Yaser
  • Ramos, Andres
  • Sanz-Bobi, Miguel A.

Abstract

This paper addresses the generation maintenance scheduling (GMS) dilemma in a deregulated power system. At first, under a centralized cost minimization framework, a GMS is formulated and set as the benchmark (cost-minimization GMS). Then, the cost-minimization is changed into a profit-maximization problem of generation companies (GENCOs) and the GMS is developed as a bi-level optimization. Karush–Kuhn–Tucker conditions are applied to transform the bi-level into a single-level mixed-integer linear problem and subsequently, Nash equilibrium is obtained as the final solution for the GMS under a deregulated market (profit-maximization GMS). Moreover, to incorporate reliability and economic regulatory constraints, two rescheduling signals (incentive and penalty) are considered as coordination processes among GENCOs and independent system operators. These signals are based on energy-not-supplied and operation cost, and ensure that the result of profit-maximization GMS is in the given reliability and social cost limits, respectively. These limits are obtained from the cost-minimization GMS. Lastly, the model is evaluated on a test system. The results demonstrate applicability and challenges in GMS problems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:3:p:1045-1057
    DOI: 10.1016/j.ejor.2017.07.008
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    References listed on IDEAS

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    Cited by:

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    2. Si, Guojin & Xia, Tangbin & Zhu, Ying & Du, Shichang & Xi, Lifeng, 2019. "Triple-level opportunistic maintenance policy for leasehold service network of multi-location production lines," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    3. Hanyu Gu & Hue Chi Lam & Thi Thanh Thu Pham & Yakov Zinder, 2023. "Heuristics and meta-heuristic to solve the ROADEF/EURO challenge 2020 maintenance planning problem," Journal of Heuristics, Springer, vol. 29(1), pages 139-175, February.
    4. Shin, Hansol & Kim, Wook, 2023. "Comparison of the centralized and decentralized environmentally constrained economic dispatch methods of coal-fired generators: A case study for South Korea," Energy, Elsevier, vol. 275(C).
    5. Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2022. "A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. Huang, Zhouchun & Zheng, Qipeng Phil, 2020. "A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1036-1051.
    7. Li, Longxi, 2021. "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework," Omega, Elsevier, vol. 102(C).
    8. Acuña, Luceny Guzmán & Ríos, Diana Ramírez & Arboleda, Carlos Paternina & Ponzón, Esneyder González, 2018. "Cooperation model in the electricity energy market using bi-level optimization and Shapley value," Operations Research Perspectives, Elsevier, vol. 5(C), pages 161-168.

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