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A model for the preventive maintenance scheduling of power plants including wind farms

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  • Perez-Canto, Salvador
  • Rubio-Romero, Juan Carlos

Abstract

This paper considers the problem of Power Plant Preventive Maintenance Scheduling (PPPMS). The goal is to evaluate which generators must stop production to be checked periodically for safety reasons. Preventive maintenance is crucial because a failure in a power plant may cause a general breakdown in an electric grid. This situation might result in a disruption of electric service to customers. The objective is to perform the problem of PPPMS from a reliability perspective, so the reliability of the system is maximized. The model presented considers the integration of wind power plants or wind farms into a traditional electric generating system comprising thermal, hydroelectric, and nuclear power units. The resulting model is categorized as an optimization problem. A case study based on a real power system is presented. Its main objective is to validate the efficiency of the proposed analysis.

Suggested Citation

  • Perez-Canto, Salvador & Rubio-Romero, Juan Carlos, 2013. "A model for the preventive maintenance scheduling of power plants including wind farms," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 67-75.
  • Handle: RePEc:eee:reensy:v:119:y:2013:i:c:p:67-75
    DOI: 10.1016/j.ress.2013.04.005
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    References listed on IDEAS

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    5. Canto, Salvador Perez, 2008. "Application of Benders' decomposition to power plant preventive maintenance scheduling," European Journal of Operational Research, Elsevier, vol. 184(2), pages 759-777, January.
    6. Remy, Emmanuel & Corset, Franck & Despréaux, Stéphane & Doyen, Laurent & Gaudoin, Olivier, 2013. "An example of integrated approach to technical and economic optimization of maintenance," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 8-19.
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    Cited by:

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    6. Khaled Alhamad & Yousuf Alkhezi & M. F. Alhajri, 2022. "Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
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    10. Lin, Boliang & Wu, Jianping & Lin, Ruixi & Wang, Jiaxi & Wang, Hui & Zhang, Xuhui, 2019. "Optimization of high-level preventive maintenance scheduling for high-speed trains," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 261-275.
    11. 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.
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    13. Khaled Alhamad & Rym M’Hallah & Cormac Lucas, 2021. "A Mathematical Program for Scheduling Preventive Maintenance of Cogeneration Plants with Production," Mathematics, MDPI, vol. 9(14), pages 1-12, July.
    14. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    15. Zhou, Yifan & Miao, Jindan & Yan, Bin & Zhang, Zhisheng, 2020. "Bio-objective long-term maintenance scheduling for wind turbines in multiple wind farms," Renewable Energy, Elsevier, vol. 160(C), pages 1136-1147.
    16. Irawan, Chandra Ade & Ouelhadj, Djamila & Jones, Dylan & Stålhane, Magnus & Sperstad, Iver Bakken, 2017. "Optimisation of maintenance routing and scheduling for offshore wind farms," European Journal of Operational Research, Elsevier, vol. 256(1), pages 76-89.
    17. Tazi, Nacef & Châtelet, Eric & Bouzidi, Youcef, 2018. "How combined performance and propagation of failure dependencies affect the reliability of a MSS," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 531-541.
    18. Shafiee, Mahmood, 2015. "Maintenance logistics organization for offshore wind energy: Current progress and future perspectives," Renewable Energy, Elsevier, vol. 77(C), pages 182-193.
    19. Sara Antomarioni & Marjorie Maria Bellinello & Maurizio Bevilacqua & Filippo Emanuele Ciarapica & Renan Favarão da Silva & Gilberto Francisco Martha de Souza, 2020. "A Data-Driven Approach to Extend Failure Analysis: A Framework Development and a Case Study on a Hydroelectric Power Plant," Energies, MDPI, vol. 13(23), pages 1-16, December.
    20. Hyung-Chul Jo & Rakkyung Ko & Sung-Kwan Joo, 2019. "Generator Maintenance Scheduling Method Using Transformation of Mixed Integer Polynomial Programming in a Power System Incorporating Demand Response," Energies, MDPI, vol. 12(9), pages 1-14, April.

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