Abstract: Aiming at the problem that wind turbine yaw bearings are susceptible to impact loads under high wind speed and high turbulence intensity conditions, which severely consumes their service life, a load-reduction yaw control strategy based on sparrow search algorithm (SSA) and active disturbance rejection control (ADRC) is proposed. The SSA is utilized to perform global optimization on the parameters of the active disturbance rejection controller, and comparative verification is conducted via the FAST-Simulink co-simulation platform. Results show that compared with the traditional PI and genetic fuzzy yaw control strategies , the proposed strategy has a significant load reduction effect under high wind speed and high turbulence conditions, with both the fatigue load and ultimate load in the X–Y plane reduced by approximately 70%. This method can effectively suppress the impact of random aerodynamic loads on the system, which has important application value for extending the service life of the yaw system.