Offshore Wind

Offshore wind energy research focuses on optimizing energy generation and minimizing operational costs through improved efficiency and reduced maintenance needs. Current research emphasizes the application of advanced technologies, including machine learning (e.g., Bayesian neural networks, YOLOv8 object detection models) and digital twins, for predictive maintenance, anomaly detection in turbine structures and power take-off systems, and improved site selection. These advancements aim to enhance the reliability, sustainability, and economic viability of offshore wind farms, contributing significantly to the global transition towards renewable energy sources.