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Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

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  • Irawan, Chandra Ade
  • Eskandarpour, Majid
  • Ouelhadj, Djamila
  • Jones, Dylan

Abstract

Scheduling maintenance routing for an offshore wind farm is a challenging and complex task. The problem is to find the best routes for the Crew Transfer Vessels to maintain the turbines in order to minimise the total cost. This paper primarily proposes an efficient solution method to solve the deterministic maintenance routing problem in an offshore wind farm. The proposed solution method is based on the Large Neighbourhood Search metaheuristic. The efficiency of the proposed metaheuristic is validated against state of the art algorithms. The results obtained from the computational experiments validate the effectiveness of the proposed method. In addition, as the maintenance activities are affected by uncertain conditions, a simulation-based optimisation algorithm is developed to tackle these uncertainties. This algorithm benefits from the fast computational time and solution quality of the proposed metaheuristic, combined with Monte Carlo simulation. The uncertain factors considered include the travel time for a vessel to visit turbines, the required time to maintain a turbine, and the transfer time for technicians and equipment to a turbine. Moreover, the proposed simulation-based optimisation algorithm is devised to tackle unpredictable broken-down turbines. The performance of this algorithm is evaluated using a case study based on a reference wind farm scenario developed in the EU FP7 LEANWIND project.

Suggested Citation

  • Irawan, Chandra Ade & Eskandarpour, Majid & Ouelhadj, Djamila & Jones, Dylan, 2021. "Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm," European Journal of Operational Research, Elsevier, vol. 289(3), pages 912-926.
    • Handle: RePEc:eee:ejores:v:289:y:2021:i:3:p:912-926
    DOI: 10.1016/j.ejor.2019.08.032
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    Cited by:

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    3. Ksciuk, Jana & Kuhlemann, Stefan & Tierney, Kevin & Koberstein, Achim, 2023. "Uncertainty in maritime ship routing and scheduling: A Literature review," European Journal of Operational Research, Elsevier, vol. 308(2), pages 499-524.
    4. Lerche, J. & Lorentzen, S. & Enevoldsen, P. & Neve, H.H., 2022. "The impact of COVID -19 on offshore wind project productivity – A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    5. 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.
    6. Xiaodong Li & Xiang Song & Djamila Ouelhadj, 2023. "A Cost Optimisation Model for Maintenance Planning in Offshore Wind Farms with Wind Speed Dependent Failure Rates," Mathematics, MDPI, vol. 11(13), pages 1-21, June.

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