Multi-objective optimisation of multifaceted maintenance strategies for wind farms
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This paper proposes a way to simultaneously optimise three aspects of maintenance strategies for wind farms: the reliability thresholds that indicate when a component needs maintenance, the priority of maintenance jobs in case there are more jobs than available maintenance teams, and the use of opportunistic maintenance. We use a multi-objective evolutionary algorithm to simultaneously minimise the overall maintenance cost and the system idle time. An empirical study using a complex stochastic simulation demonstrates the benefit of such a multifaceted maintenance strategy over strategies that only consider some aspects.
本研究提出一种可同时优化风电场运维策略三大维度的方法:判定部件需开展运维的可靠性阈值、当运维任务总量超出可用运维团队承载能力时的运维任务优先级调度规则,以及机会性运维的实施策略。本研究采用多目标进化算法,以同时实现总运维成本与系统停机时长的最小化。通过复杂随机模拟开展的实证研究表明,相较仅考虑部分维度的运维策略,该多维度运维方案具备显著优势。



