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Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System

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  • Peyman Mazidi

    (Institute for Research in Technology (IIT), Comillas Pontifical University, 28015 Madrid, Spain
    Electric Power and Energy Systems Department, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden)

  • Yaser Tohidi

    (Electric Power and Energy Systems Department, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden)

  • Miguel A. Sanz-Bobi

    (Institute for Research in Technology (IIT), Comillas Pontifical University, 28015 Madrid, Spain)

Abstract

This paper proposes a model for strategic maintenance scheduling of offshore wind farms (SMSOWF) in a deregulated power system. The objective of the model is to plan the maintenance schedules in a way to maximize the profit of the offshore wind farm. In addition, some network constraints, such as transmission lines capacity, and wind farm constraints, such as labor working shift, wave height limit and wake effect, as well as unexpected outages, are included in deterministic and stochastic studies. Moreover, the proposedmodel provides theability to incorporate information from condition monitoring systems. SMSOWF is formulated through a bi-level formulation and then transformed into a single-level through Karush–Kuhn–Tucker conditions. The model is validated through a test system, and the results demonstrate applicability, advantages and challenges of harnessing the full potential of the model.

Suggested Citation

  • Peyman Mazidi & Yaser Tohidi & Miguel A. Sanz-Bobi, 2017. "Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System," Energies, MDPI, vol. 10(3), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:313-:d:92238
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    References listed on IDEAS

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    Cited by:

    1. Peyman Mazidi & Miguel A Sanz Bobi & Ebrahim Shayesteh & Patrik Hilber, 2017. "Impact of health indicators on maintenance management and operation of power systems," Journal of Risk and Reliability, , vol. 231(6), pages 716-731, December.
    2. Orlando Duran & Andrea Capaldo & Paulo Andrés Duran Acevedo, 2017. "Lean Maintenance Applied to Improve Maintenance Efficiency in Thermoelectric Power Plants," Energies, MDPI, vol. 10(10), pages 1-21, October.
    3. Ralf Stetter, 2020. "Approaches for Modelling the Physical Behavior of Technical Systems on the Example of Wind Turbines," Energies, MDPI, vol. 13(8), pages 1-27, April.
    4. Walgern, Julia & Peters, Lennart & Madlener, Reinhard, 2017. "Economic Evaluation of Maintenance Strategies for Offshore Wind Turbines Based on Condition Monitoring Systems," FCN Working Papers 8/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    5. Stojiljković, Mirko M., 2017. "Bi-level multi-objective fuzzy design optimization of energy supply systems aided by problem-specific heuristics," Energy, Elsevier, vol. 137(C), pages 1231-1251.
    6. Luciano C. Siebert & Adriana Sbicca & Alexandre Rasi Aoki & Germano Lambert-Torres, 2017. "A Behavioral Economics Approach to Residential Electricity Consumption," Energies, MDPI, vol. 10(6), pages 1-18, June.
    7. Ade Irawan, Chandra & Starita, Stefano & Chan, Hing Kai & Eskandarpour, Majid & Reihaneh, Mohammad, 2023. "Routing in offshore wind farms: A multi-period location and maintenance problem with joint use of a service operation vessel and a safe transfer boat," European Journal of Operational Research, Elsevier, vol. 307(1), pages 328-350.
    8. 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.

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