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Modelling and simulation of operation and maintenance strategy for offshore wind farms based on multi-agent system

Author

Listed:
  • M’hammed Sahnoun

    (CESI – IRISE Laboratory)

  • David Baudry

    (CESI – LUSINE Laboratory)

  • Navonil Mustafee

    (University of Exeter)

  • Anne Louis

    (CESI – IRISE Laboratory)

  • Philip Andi Smart

    (University of Exeter)

  • Phil Godsiff

    (University of Exeter)

  • Belahcene Mazari

    (CESI – IRISE Laboratory)

Abstract

Maintenance of offshore wind turbines is a complex and costly undertaking which acts as a barrier to the development of this source of energy. Factors such as the size of the turbines, the size of the wind farms, their distance from the coast and meteorological conditions make it difficult for the stakeholders to select the optimal maintenance strategy. With the objective of reducing costs and duration of such operations it is important that new maintenance techniques are investigated. In this paper we propose a hybrid model of maintenance that is based on multi-agent systems; this allows for the modelling of systems with dynamic interactions between multiple parts. A multi-criteria decision algorithm has been developed to allow analysis and selection of different maintenance strategies. A cost model that includes maintenance action cost, energy loss and installation of monitoring system cost has been presented. For the purposes of this research we have developed a simulator using NetLogo software and have provided experimental results. The results show that employing the proposed hybrid maintenance strategy could increase wind farm productivity and reduce maintenance cost.

Suggested Citation

  • M’hammed Sahnoun & David Baudry & Navonil Mustafee & Anne Louis & Philip Andi Smart & Phil Godsiff & Belahcene Mazari, 2019. "Modelling and simulation of operation and maintenance strategy for offshore wind farms based on multi-agent system," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2981-2997, December.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:8:d:10.1007_s10845-015-1171-0
    DOI: 10.1007/s10845-015-1171-0
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Niemi, Arto & Skobiej, Bartosz & Kulev, Nikolai & Sill Torres, Frank, 2024. "Modeling offshore wind farm disturbances and maintenance service responses within the scope of resilience," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Saleh, Ali & Chiachío, Manuel & Salas, Juan Fernández & Kolios, Athanasios, 2023. "Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. A. Khatab & C. Diallo & E.-H. Aghezzaf & U. Venkatadri, 2022. "Optimization of the integrated fleet-level imperfect selective maintenance and repairpersons assignment problem," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 703-718, March.
    4. Phong B. Dao, 2021. "Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems," Energies, MDPI, vol. 14(2), pages 1-17, January.
    5. Hajej Zied & Rezg Nidhal & Kammoun Mohamed Ali & Bouzouba Maryem, 2024. "Improved maintenance strategy for the wind turbine system under operating and climatic conditions," Journal of Risk and Reliability, , vol. 238(2), pages 349-365, April.
    6. McMorland, Jade & Flannigan, Callum & Carroll, James & Collu, Maurizio & McMillan, David & Leithead, William & Coraddu, Andrea, 2022. "A review of operations and maintenance modelling with considerations for novel wind turbine concepts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    7. Diego Francisco Larios & Enrique Personal & Antonio Parejo & Sebastián García & Antonio García & Carlos Leon, 2020. "Operational Simulation Environment for SCADA Integration of Renewable Resources," Energies, MDPI, vol. 13(6), pages 1-37, March.
    8. Ren, Zhengru & Verma, Amrit Shankar & Li, Ye & Teuwen, Julie J.E. & Jiang, Zhiyu, 2021. "Offshore wind turbine operations and maintenance: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).

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