LAUSR

Abstract This paper is devoted to an active power control architecture for a wind farm based on model predictive control (MPC) combined with wind turbine (WT) state classification. The objectives include wind farm power reference tracking and improving the response to power grid scheduling. Conventionally, a PI controller with a proportional distribution block is applied at the wind farm control level. However, the strategy proposed in this paper replaces the PI controller with MPC controllers and adds another power distribution block before the MPC controllers. Based on the WT state classification according to different wind speed ranges, the equivalent models of WTs for the corresponding MPC controllers are built. Besides, a proper allocation algorithm for the introduced distribution block is designed. With the classification concept, the response speed is significantly improved. The proposed control strategy is tested on a wind farm with 14 WTs using MATLAB\Simulink simulation and the effectiveness is verified.