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

Yifan Zhou, Jindan Miao, Bin Yan and Zhisheng Zhang

Renewable Energy, 2020, vol. 160, issue C, 1136-1147

Abstract: 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.

Keywords: Maintenance scheduling; Bio-objective optimisation; Wind turbines; Weather condition modelling (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:160:y:2020:i:c:p:1136-1147

DOI: 10.1016/j.renene.2020.07.065

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