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Sensitivity of Risk-Based Maintenance Planning of Offshore Wind Turbine Farms

机译:海上风电场基于风险的维护计划的敏感性

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摘要

Inspection and maintenance expenses cover a considerable part of the cost of energy from offshore wind turbines. Risk-based maintenance planning approaches are a powerful tool to optimize maintenance and inspection actions and decrease the total maintenance expenses. Risk-based planning is based on many input parameters, which are in reality often not completely known. This paper will assess the cost impact of this incomplete knowledge based on a case study following risk-based maintenance planning. The sensitivity study focuses on weather forecast uncertainties, incomplete knowledge about the needed repair time on the site as well as uncertainties about the operational range of the boat and helicopter used to access the broken wind turbine. The cost saving potential is estimated by running Crude Monte Carlo simulations. Furthermore, corrective and preventive (scheduled and condition-based) maintenance strategies are implemented. The considered case study focuses on a wind farm consisting of ten 6 MW turbines placed 30 km off the Danish North Sea coast. The results show that the weather forecast is the uncertainty source dominating the maintenance expenses increase when considering risk-based decision-making uncertainties. The overall maintenance expenses increased by 70% to 140% when considering uncertainties directly related with risk-based maintenance planning.
机译:检查和维护费用涵盖了来自海上风力涡轮机的大部分能源成本。基于风险的维护计划方法是优化维护和检查措施并减少总维护费用的强大工具。基于风险的计划是基于许多输入参数的,实际上,这些输入参数通常并不完全为人所知。本文将根据基于风险的维护计划进行案例研究,评估这种不完整知识的成本影响。敏感性研究的重点是天气预报的不确定性,对现场所需维修时间的不完全了解以及用于接近破损的风力涡轮机的船只和直升机的操作范围的不确定性。通过运行Crude Monte Carlo模拟可以估算出节省成本的潜力。此外,还实施了纠正性和预防性(计划性和基于状况的)维护策略。经过考虑的案例研究集中在一个风力发电场,该风力发电场由十个6兆瓦的涡轮机组成,它们位于丹麦北海海岸30公里处。结果表明,在考虑基于风险的决策不确定性时,天气预报是不确定性来源,是维护费用增加的主要来源。当考虑与基于风险的维护计划直接相关的不确定性时,总体维护费用增加了70%至140%。

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