Study on the yaw-based wake steering control considering dynamic flow characteristics for wind farm power improvement

Abstract

Wake steering is one of the wind farm control strategies that can effectively reduce wake losses and increase power generation. Upstream wind turbines are set with yaw misalignment angles to deflect their wake away from downstream wind turbines, which will alleviate the wake effect. Currently, the yaw misalignment angles of the wind turbines are optimized through CFD or analytical wake models with a fixed inflow wind direction. However, wind turbines operate in rapidly changing wind directions where they cannot immediately track the optimized yaw misalignment angles owing to the slow yaw mechanism as expected. Therefore, a dynamic yaw control method is proposed in this study with the aim of balancing the energy gain and the number of yaw movements. Firstly, in order to improve efficiency, the yaw misalignment set points of wind turbines are optimized with different wind conditions based on the steady wake model. Then, we illustrate the procedure for determining the yaw misalignment angles for dynamic wind conditions. Finally, the performance of the yaw controller under the measured inflow condition is analyzed for the case of two-turbine array. It was found that the optimized yaw misalignment angles based on the steady model are applied to the dynamic control under changing wind direction, where the energy gain does not reach the estimated value using the static optimized control.