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Service operation vessels for offshore wind farm maintenance: Optimal stock levels

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  • Neves-Moreira, Fábio
  • Veldman, Jasper
  • Teunter, Ruud H.

Abstract

Service operation vessels are becoming the dominant mode for the maintenance of most offshore wind farms. To minimize turbine downtime, it is essential to bring the right components to the wind farm, while budget and volume constraints prohibit having excess inventories on board. This setting can be interpreted as a repair kit problem, which seeks to define a set of components that may be necessary for on-site maintenance operations in a given time period during which emergency resupply is costly. Current repair kit problem approaches however, do not cater sufficiently for some of the characteristics of offshore wind farm maintenance, including weather-dependent deterioration and the possibility to perform emergency resupplies. We propose mixed-integer programming models both to determine (tactical model) and validate (operational model) repair kits when maintenance operations are performed under different weather conditions. The models are flexible enough to be used with real world data considering multiple turbines composed of different deteriorating components, service operation vessels characteristics (speed and volumetric capacity), different weather conditions, and emergency resupplies. An important feature of this approach is its ability to consider detailed maintenance and vessel routing operations to test and validate repair kits in realistic wind farm environments. We provide valuable insights on the composition of repair kits and on relevant business indicators for a set of different scenarios. The practical implications are that repair kits should be adapted depending on weather forecasts and that considerable downtime reductions can be achieved by allowing emergency resupplies.

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  • Neves-Moreira, Fábio & Veldman, Jasper & Teunter, Ruud H., 2021. "Service operation vessels for offshore wind farm maintenance: Optimal stock levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:rensus:v:146:y:2021:i:c:s1364032121004470
    DOI: 10.1016/j.rser.2021.111158
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    3. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

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