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A metaheuristic solution method for optimizing vessel fleet size and mix for maintenance operations at offshore wind farms under uncertainty

机译:一种在不确定条件下优化海上风电场维修作业的船队规模和混合的元启发式解决方案

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摘要

Maintenance operations at offshore wind farms are challenging due to the offshore element; maintenance technicians and spare parts need to be transported from an onshore port or offshore station to the individual wind farm components in need of maintenance. The vessel resources needed to support these maintenance tasks constitute a major part of the total maintenance costs, and hence up-keeping an optimal vessel fleet and corresponding deployment is essential to reduce cost-of-energy. This paper introduces a metaheuristic solution method to determine cost-efficient vessel fleets to support maintenance tasks at offshore wind farms under uncertainty. It considers weather conditions and failures leading to corrective maintenance tasks as stochastic parameters, and evaluates candidate solutions by a simulation program. The solution method has been incorporated in a decision support tool. Computational experiments, including comparison of results with an exact solution method, illustrate that the decision support tool can be used to provide near-optimal solutions within acceptable computational time.
机译:由于海上因素,海上风电场的维护操作具有挑战性。维护技术人员和备件需要从陆上港口或近海站运输到需要维护的各个风电场组件。支持这些维护任务所需的船舶资源占总维护成本的主要部分,因此维持最佳的船队和相应的部署对于降低能源成本至关重要。本文介绍了一种元启发式解决方案方法,以确定具有成本效益的船队,以支持不确定性下海上风电场的维护任务。它将导致纠正性维护任务的天气条件和故障视为随机参数,并通过模拟程序评估候选解决方案。解决方案方法已合并到决策支持工具中。计算实验(包括使用精确解法进行结果比较)表明,决策支持工具可用于在可接受的计算时间内提供近乎最优的解。

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