Component-level Wind Farm Maintenance Considering Seasonal Uncertainties

Global climate change has made maintaining wind energy systems more challenging. Wind farm reliability and maintenance management significantly influence the cost of wind energy. However, existing research on maintenance approaches for wind farms often overlooks the impact of weather-related factors, leading to inaccuracies. This paper addresses this issue by constructing a novel predictive maintenance optimization model considering seasonal uncertainties. Furthermore, the maintenance decision-making process considers component-level repairs, economic dependencies, and various failure modes of wind turbines for a comprehensive approach. Consequently, the optimal maintenance policy derived from the proposed method achieves greater accuracy compared to previous methods. A case study, utilizing a dataset from actual wind farms, is presented to demonstrate and validate the proposed maintenance optimization method.