Active yaw control optimization of wind turbines in wind farms considering multi-scenario wind speed and direction

Active optimization of the yaw angle of wind turbines can improve overall power generation for the wind farm. In this paper, an active yaw control strategy with a yaw-angle exceedance penalty is proposed, and the feasibility of the approach is verified by four cases of single-scenario and multi-scenarios. First, the double Gaussian model with the yaw deflection method is utilized to predict the wake loss of a single turbine. Then, a sum-of-squares superposition model is utilized to evaluate the superposition effect of multiple turbine wake flows. Then, the particle swarm optimization algorithm with a time-varying inertia factor is optimized for single-scenario wind turbine yaw optimization, and the results are used as the initial solution for multi-scenarios. Finally, a penalty system for yaw-angle exceedance is established to globally optimize turbine yaw angle for multi-scenarios. The results show that the single-scenario yaw optimization can improve the power efficiency by 3.13%–8.61%, and the multi-scenarios active yaw optimization can improve the power efficiency by 0.58%–0.63%. The proposed method can be used for multi-scenario yaw optimization in real wind farms to achieve a balance between power generation enhancement and fatigue load reduction.