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Testing the robustness of optimal access vessel fleet selection for operation and maintenance of offshore wind farms

机译:测试用于海上风电场运营和维护的最佳通道船队选择的稳健性

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摘要

Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. This paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimal vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels' limiting significant wave height for turbine access. This is also the parameter with the greatest discrepancy between the tools, implying that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed.
机译:优化海上风电场的运维(O&M)和物流策略,意味着选择船队进行运维的决策问题。可以将不同的战略决策支持工具应用于此问题,但是有关输入数据和建模假设的不确定性仍然很大。本文旨在通过比较四种仿真工具,一种数学优化工具和一种基于分析电子表格的工具来调查并最终减少这种不确定性,这些工具可用于选择运维通道船队,从而最大程度地降低参考风电场的运维总成本。比较表明,这些工具通常就最佳船队达成一致,但就运维总成本而言,仅部分就不同船队的相对排名达成一致。测试了船队选择对各种输入数据假设的鲁棒性,并且发现该排名对船只限制涡轮访问的重要波高特别敏感。这也是工具之间差异最大的参数,这意味着准确量化和建模此参数至关重要。该排名对涡轮机故障率和船舶日费率较为敏感,但对电价和船舶运输速度较不敏感。

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