Optimal chartering decisions for vessel fleet to support offshore wind farm maintenance operations

Mingxin Li*, Bas Bijvoet, Kangjie Wu, Xiaoli Jiang, Rudy R. Negenborn

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Offshore wind energy is expected to be the most significant source of future electricity supply in Europe. Offshore wind farms are located far from the shores, requiring a fleet of various types of vessels to access sites when maintaining offshore wind turbines. The employment of the vessels is costly, accounting for the majority of the total O&M costs for offshore wind energy. Therefore, configuring the size and mix of the vessel fleet to support maintenance operations in a cost-effective manner is an issue of importance to enhance economics of offshore wind sector. In this paper, a discrete event simulation based model is proposed to present how a mixed vessel fleet with the specific configuration, including crew transfer vessels, field support vessels, and heavy lift vessels, performs maintenance for an offshore wind farm. The economic performance of the vessel fleet under a predetermined condition-based opportunistic maintenance strategy is investigated by using the model. A metaheuristic algorithm, simulated annealing, is employed to find the optimal fleet size and mix to make leasing decisions with the minimum costs. The performance of the developed approaches is evaluated by using a generic offshore wind farm in the North Sea. The sensitivity analysis is performed to investigate the most influential O&M factors.

Original languageEnglish
Article number117202
Number of pages18
JournalOcean Engineering
Volume298
DOIs
Publication statusPublished - 2024

Funding

This research is financially supported by the grant awarded within NWO-KIC as part of the project “Holi-DOCTOR: Holistic framework for DiagnOstiCs and moniTORing of wind turbine blades” (KICH1.ED02.20.004), and the scholarship from China Scholarship Council (CSC) under the Grant CSC NO. 201906680095.

Keywords

  • Condition-based opportunistic maintenance
  • Offshore wind energy
  • Operation and maintenance
  • Vessel fleet

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