Research On Dynamic Load Control Strategy Of Drive Train In Wind Turbine

Under the situation that the unit capacity and the total capacity of wind turbines are increasing, the effect of wind shear, turbulence, transmission damping and other objective factors are constantly increasing, how to effectively reduce the wind turbine especially the loads of important part in the transmission system become a difficult problem in wind power.Therefore, non-linear torque control strategy and model predictive control(MPC) based on the torque ripple suppression strategy are proposed in tow operation areas.When it is below the rated wind speed, maximum Power Point Tracking and the loads of the drive train in the doubly-fed wind turbines are analyzed, online dynamic prediction method is used as a reference, the wind speed is predicted by Kalman filter and Newton iteration, the Kalman filter is the input power Torque wind wheel speed, nonlinear control(NC) is used, to reduce the power fluctuation, increase the output power quality and reduce driveline torsional loads through the timely tracking optimal torque.When it is above rated wind speed, the loads of drive train in wind turbines due to the randomness of wind speed and the uncertainty of wind turbines are analyzed, and the nonlinear uncertainties in wind turbines are compensated by using the Kalman filter, the controller based on model predictive control(MPC) is designed to increase the controlling accuracy, reduce the equivalent rotate speed in low speed shaft, reduce the load of gearbox and prolong the lifespan of wind turbine.In order to research the proposed control strategy, the traditional PI control strategy and proposed control strategy has carried on the simulation and comparison analysis using FAST/MATLAB software with doubly-fed wind turbine, the results show that the proposed control strategy for the reduction of dynamic load of drive train in wind turbines is effective.