Active yaw control strategy for a hybrid offshore wind farm under typical wind conditions

This paper proposes an active yaw control strategy for the hybrid offshore wind farms to enhance the offshore wind farm's total power generation. Firstly, a three-dimensional yawed wake model is applied for calculating the power output of different types of wind turbines under active yaw control and the whole offshore wind farm. Next, the architecture of the proposed active yaw control system is demonstrated, and an optimization model is formulated. To solve this optimization problem, the quantum genetic algorithm is employed. Simulation results on a simplified layout of three wind turbines in a row and the Guishan offshore wind farm under three typical wind conditions demonstrate that the proposed strategy can effectively mitigate the inner-array wake effect in hybrid offshore wind farms. The results also suggest that applying active yaw control in the non-dominant wind directions and for small wind turbines in a hybrid offshore wind farm should be prioritized which yields the most significant improvement of 24.89 % in overall offshore wind farm power output. Additionally, the quantum genetic algorithm is shown to be an efficient and robust optimization tool for solving the optimal active yaw control problem in hybrid offshore wind farms with computation time of 17.83 min, 20.12 min, and 19.30 min in the three test cases, respectively.