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A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract

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  • Huang, Zhouchun
  • Zheng, Qipeng Phil

Abstract

A preventive maintenance scheduling problem is studied on behalf of generation companies (GENCOs) with natural gas power plants, while taking into account their signed natural gas contracts and the opportunities of purchasing and selling natural gas in the spot market. This paper considers the uncertain prices of both natural gas and electricity in the spot market, and proposes a multistage stochastic mixed integer programming (MSMIP) model seeking the optimal operations regarding maintenance outage scheduling and natural gas trading. Large-scale MSMIP problems suffer not only the curse of dimensionality, but also computational difficulties with both discrete and continuous variables at each stage. To this respect, this paper leverages the progressive hedging algorithm based on scenario-based decomposition to solve large MSMIP problems. The solutions obtained from the algorithm exhibit promising quality under our numerical studies. Due to the independence among all the subproblems after the decomposition, the algorithm is amenable to parallel computing, which leads to faster convergence as demonstrated in the numerical results. Computational experiments also show that it is beneficial to use MSMIP while considering both maintenance planning and natural gas contracting. In addition, the results also indicate the GENCOs with a larger number of small generators perform better than those with a smaller number of big generators.

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  • 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.
    • Handle: RePEc:eee:ejores:v:287:y:2020:i:3:p:1036-1051
    DOI: 10.1016/j.ejor.2020.03.036
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    4. Kim, Seon-Yong & Kim, Man-Keun & Choi, Myung Hwan & Kim, Dae-Wook, 2024. "Optimal preventive maintenance: Balancing reliability and costs in the electricity market," Energy Policy, Elsevier, vol. 194(C).
    5. Aoyu Fan & Zhouchun Huang & Qipeng Zheng & Xiaodong Luo, 2025. "A two-stage stochastic programming approach for generation and transmission maintenance scheduling with risk management," Computational Optimization and Applications, Springer, vol. 92(3), pages 787-809, December.
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    7. Ding, Yutong & Xia, Tangbin & Wang, Yu & Zhang, Kaigan & Li, Yaping & Chen, Zhen & Xi, Lifeng, 2025. "A multi-stage stochastic programming for joint condition-based replacement and spare parts ordering towards complex manufacturing system with uncertain lead times," Reliability Engineering and System Safety, Elsevier, vol. 264(PB).
    8. Zhong, Zhiming & Fan, Neng & Wu, Lei, 2024. "Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty," European Journal of Operational Research, Elsevier, vol. 318(1), pages 179-199.
    9. 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.
    10. Xiaoqing Liu & Gongli Luo & Xinsheng Xu, 2022. "Optimal Purchasing Decisions with Supplier Default in Portfolio Procurement," Mathematics, MDPI, vol. 10(17), pages 1-10, September.
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