A comprehensive review of artificial intelligence applications in wind energy power generation

Renewable energy sources have seen significant improvements in the past 50 years, with wind energy being a particularly promising solution to the global energy crisis. Efficient wind generation relies on RAMS (reliability, availability, maintainability, and safety), which has been the focus of numerous studies. In recent years, data-driven approaches and machine learning-based methods have helped to enhance the operation and maintenance (O&M) of wind farms. These techniques can predict potential failures, power shortages, damages, and other issues before they cause shutdowns. The paper provides a comprehensive review of studies conducted between 2015 and 2024, covering output power prediction, fault detection, condition monitoring, and blade icing detection. The study also includes simplified explanations to help fellow scholars and those in the academic domain better understand the material.