Optimizing yaw angles for improved power generation in offshore wind farms: A statistical approach

Abstract

Aerodynamic interactions among wind turbines diminish power generation in offshore wind farms. Adjusting a turbine’s yaw angle, deliberately misaligned from the wind direction, mitigates energy losses from wake effects, thereby enhancing overall power generation. This study employs advanced wind farm simulation software for numerical simulations to compute the optimal yaw angle and associated percentage power gain for three offshore wind turbines under varying conditions, encompassing turbine models, wind speeds, turbulence intensities, and layouts. Two polynomial regression models and one decision tree classification model are developed to estimate the yaw angle and percentage power gain based on these conditions. These models are computationally efficient, integrating previously unconsidered predictors, and facilitating assessment of predictor impacts on yaw angle and power gain. Moreover, they enable real-time adjustment of turbine nacelle direction, positioning them for effective deployment at scale in offshore wind farms. Implementing these models is anticipated to extend and facilitate the use of turbine yawing as a strategy to enhance energy generation, providing computationally efficient tools for optimizing power generation in ocean wind farms.