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Opportunistic condition-based maintenance optimization for electrical distribution systems

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  • Wang, Yifei
  • He, Rui
  • Tian, Zhigang

Abstract

The major goal of maintenance decision-making for electrical distribution systems (EDS) is to find maintenance policy with minimum costs, and this has been the top priority requirement for many power companies. To this aim, an opportunistic condition-based maintenance (CBM) policy is proposed for EDS in this work and incorporated into the Monte Carlo simulation (MCS) framework for maintenance decision-making. In contrast to reported works, three main contributions are summarized. First, it is the first time to design maintenance policies for EDSs according to their inspection states with the consideration of opportunistic maintenance. Second, invalid failure data in EDS, possibly caused by unanticipated events, are measured and mitigated by statistical matching based on the maximum mean discrepancy (MMD) before assessing the benefits of maintenance decisions. Third, the influence of the structural dependency is modeled in the CBM policy, which widely exists in EDSs but is rarely considered in previous works. A case study using the dataset collected from a real EDS is provided to demonstrate and validate the proposed maintenance optimization method.

Suggested Citation

  • Wang, Yifei & He, Rui & Tian, Zhigang, 2023. "Opportunistic condition-based maintenance optimization for electrical distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
  • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s095183202300176x
    DOI: 10.1016/j.ress.2023.109261
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    1. Carla Gonçalves Machado & Mats Peter Winroth & Elias Hans Dener Ribeiro da Silva, 2020. "Sustainable manufacturing in Industry 4.0: an emerging research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1462-1484, March.
    2. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    3. Fares, Robert L. & King, Carey W., 2017. "Trends in transmission, distribution, and administration costs for U.S. investor-owned electric utilities," Energy Policy, Elsevier, vol. 105(C), pages 354-362.
    4. Liu, Bin & Xu, Zhengguo & Xie, Min & Kuo, Way, 2014. "A value-based preventive maintenance policy for multi-component system with continuously degrading components," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 83-89.
    5. Zhou, Xiaojun & Huang, Kaimin & Xi, Lifeng & Lee, Jay, 2015. "Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 231-237.
    6. Kowal, Karol & Torabi, Mina, 2021. "Failure mode and reliability study for Electrical Facility of the High Temperature Engineering Test Reactor," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    7. Zhou, P. & Yin, P.T., 2019. "An opportunistic condition-based maintenance strategy for offshore wind farm based on predictive analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 1-9.
    8. Andrews, John & Prescott, Darren & De Rozières, Florian, 2014. "A stochastic model for railway track asset management," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 76-84.
    9. Azadeh, A. & Asadzadeh, S.M. & Salehi, N. & Firoozi, M., 2015. "Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 357-368.
    10. He, Rui & Tian, Zhigang & Wang, Yifei & Zuo, Mingjian & Guo, Ziwei, 2023. "Condition-based maintenance optimization for multi-component systems considering prognostic information and degraded working efficiency," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    11. Vu, Hai Canh & Do, Phuc & Fouladirad, Mitra & Grall, Antoine, 2020. "Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    12. Salman, Abdullahi M. & Li, Yue & Bastidas-Arteaga, Emilio, 2017. "Maintenance optimization for power distribution systems subjected to hurricane hazard, timber decay and climate change," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 136-149.
    13. Ding, Fangfang & Tian, Zhigang, 2012. "Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds," Renewable Energy, Elsevier, vol. 45(C), pages 175-182.
    14. Hughes, William & Zhang, Wei & Bagtzoglou, Amvrossios C. & Wanik, David & Pensado, Osvaldo & Yuan, Hao & Zhang, Jintao, 2021. "Damage modeling framework for resilience hardening strategy for overhead power distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    15. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2015. "Multi-level predictive maintenance for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 83-94.
    16. Zhang, Nan & Cai, Kaiquan & Zhang, Jun & Wang, Tian, 2022. "A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    17. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2016. "Clustering condition-based maintenance for systems with redundancy and economic dependencies," European Journal of Operational Research, Elsevier, vol. 251(2), pages 531-540.
    18. Zhang, Nan & Fouladirad, Mitra & Barros, Anne & Zhang, Jun, 2020. "Condition-based maintenance for a K-out-of-N deteriorating system under periodic inspection with failure dependence," European Journal of Operational Research, Elsevier, vol. 287(1), pages 159-167.
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    1. Dinh, Duc-Hanh & Do, Phuc & Iung, Benoit & Nguyen, Pham-The-Nhan, 2024. "Reliability modeling and opportunistic maintenance optimization for a multicomponent system with structural dependence," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Qi, Faqun & Huang, Meiqi, 2024. "Joint optimization of maintenance and spares inventory policy for a series-parallel system considering dependent failure processes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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