Wind Turbine

Wind turbines are crucial for renewable energy generation, and research focuses on optimizing their performance, extending their lifespan, and minimizing operational costs. Current research employs various machine learning models, including deep learning architectures like convolutional neural networks, recurrent neural networks (LSTMs), and graph transformers, to improve condition monitoring, predict power output, and optimize control strategies (e.g., pitch and yaw control). These advancements in data-driven modeling and AI-powered diagnostics are significantly impacting the wind energy industry by enabling more efficient maintenance, reducing downtime, and maximizing energy production.