Neural Network Dynamic Load Control Of Double-Fed Wind Turbine Drive-Train

Load has become a problem which has to take account of a larger capacity and flexibility; control strategy can improve the capture rate and reduce the dynamic load. A torque controller is designed based on neural network control in this paper. The method adjusts the rotor speed and improves the damping of the drive train for a 5 MW above the rated wind speed based on the state space matrix. The simulation results by MATLAB and FAST software shows this method can reduce the dynamic loads and improve operational life and stability.