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Bio-objective long-term maintenance scheduling for wind turbines in multiple wind farms

机译:多个风电场风力涡轮机的生物目标长期维护调度

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Maintenance scheduling (MS) for wind turbines (WTs) is an emerging investigation area in recent years. The MS of WTs is more complex than that of traditional thermal generators, because maintenance activities of WTs are affected by stochastic weather conditions, e.g., wind speed and precipitation. This paper proposes a long-term MS method to obtain the joint preventive maintenance plan during the whole warranty period of WTs on multiple wind farms. Both the labour cost and production loss are used as objective functions of the MS. Historical weather data are analysed, and a statistical model is developed to describe the weather conditions. Then, the MS problem is formulated compactly as a mixed integer linear programming model. Finally, a detailed practical case study is demonstrated to validate the effectiveness of the proposed MS method. The result confirms that cost-effective joint preventive maintenance (PM) plans of three wind farms can be derived through the proposed MS method. Compared with the periodic PM plan, the expected labour cost and production loss are reduced by approximately 30% and 20%, respectively. (C) 2020 Elsevier Ltd. All rights reserved.
机译:风力涡轮机(WTS)的维护调度(MS)是近年来新兴调查区。 WTS的MS比传统的热发电机更复杂,因为WTS的维护活动受到随机天气条件的影响,例如风速和降水。本文提出了长期MS方法,以便在多个风电场的全部保修期间获得联合预防性维护计划。劳动力成本和生产损失都用作MS的客观函数。分析历史天气数据,开发了统计模型来描述天气状况。然后,将MS问题紧凑地配制为混合整数线性编程模型。最后,证明了详细的实际案例研究以验证所提出的MS方法的有效性。结果证实,可以通过所提出的MS方法来得出具有三个风电场的具有成本效益的联合预防性维护(PM)计划。与定期PM计划相比,预期的劳动力成本和生产损失分别降低了约30%和20%。 (c)2020 elestvier有限公司保留所有权利。

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