Optimal chartering decisions for vessel fleet to support offshore wind farm maintenance operations
Li, Mingxin and Bijvoet, Bas and Wu, Kangjie and Jiang, Xiaoli and Negenborn, Rudy R. (2024) Optimal chartering decisions for vessel fleet to support offshore wind farm maintenance operations. Ocean Engineering, 298. 117202. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2024.117202)
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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.
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Item type: Article ID code: 88263 Dates: DateEvent15 April 2024Published22 February 2024Published Online18 February 2024AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 27 Feb 2024 11:58 Last modified: 19 Nov 2024 01:19 URI: https://strathprints.strath.ac.uk/id/eprint/88263