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Optimal Preventive Maintenance Scheduling for Wind Turbines under Condition Monitoring

Author

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  • Quanjiang Yu

    (Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-42196 Gothenburg, Sweden
    Current address: Ericsson AB, SE-41756 Gothenburg, Sweden.)

  • Pramod Bangalore

    (Greenbyte AB, SE-41109 Gothenburg, Sweden)

  • Sara Fogelström

    (Department of Electrical Engineering, Chalmers University of Technology, SE-42196 Gothenburg, Sweden)

  • Serik Sagitov

    (Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-42196 Gothenburg, Sweden)

Abstract

Renewable energy sources, such as wind and solar, are positioned to play a pivotal role in future energy systems. In this paper, we propose a mathematical model for calculating and regularly updating the next preventive maintenance plan for a wind farm. Our optimization criterion considers various factors, including the current ages of key components, major maintenance costs, eventual energy production losses, and available data monitoring the condition of the wind turbines. Employing Cox proportional hazards analysis, we develop a comprehensive approach that accounts for the current ages of critical components, significant maintenance costs, potential energy production losses, and data collected from monitoring the condition of wind turbines. We illustrate the effectiveness of our approach through a case study based on data collected from multiple wind farms in Sweden. Our results demonstrate that preventive maintenance planning yields positive effects, particularly when the wind turbine components in question have significantly shorter lifespans than the turbine itself.

Suggested Citation

  • Quanjiang Yu & Pramod Bangalore & Sara Fogelström & Serik Sagitov, 2024. "Optimal Preventive Maintenance Scheduling for Wind Turbines under Condition Monitoring," Energies, MDPI, vol. 17(2), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:2:p:280-:d:1313782
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    References listed on IDEAS

    as
    1. Bangalore, P. & Patriksson, M., 2018. "Analysis of SCADA data for early fault detection, with application to the maintenance management of wind turbines," Renewable Energy, Elsevier, vol. 115(C), pages 521-532.
    2. P J Vlok & J L Coetzee & D Banjevic & A K S Jardine & V Makis, 2002. "Optimal component replacement decisions using vibration monitoring and the proportional-hazards model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(2), pages 193-202, February.
    3. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    4. Zhang, Chen & Gao, Wei & Guo, Sheng & Li, Youliang & Yang, Tao, 2017. "Opportunistic maintenance for wind turbines considering imperfect, reliability-based maintenance," Renewable Energy, Elsevier, vol. 103(C), pages 606-612.
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