The Research Of Maximum Power Point Tracking For Wind Power Based On Elman Neural Network

With the widely application of the variable speed constant frequency wind generating set, how to improve the efficiency of wind energy, realizing the maximization of power generation has become the key problem in the wind power generation technology. In order to maximize the use of wind power, the effective ways to improve the efficiency of variable speed constant frequency wind power generation is under the best speed, how to control the operation of wind turbine research is the study of the maximum power point tracking control method, so that the maximum capture of wind energy.Based on the variable speed constant frequency doubly-fed asynchronous wind power generation system as the main research content, the maximum wind power tracking control first wind power development at home and abroad were reviewed and the development situation of wind power, wind power related technical development level and the research status of maximum wind energy tracking technology, combined with the variable speed constant frequency wind power generation system, the basic theory of specific analysis of the operation mechanism of the wind turbine, wind power generation system of operating characteristics and the principle of maximum wind power tracking and control methods.) was proposed based on RBF and Elman neural network algorithm of maximum power point, mainly describes the principle of the method and control mode, and designed a controller based on RBF and Elman neural network, RBF neural network controller by adjusting the motor speed, speed has been running at maximum speed, to capture the maximum power point, and the Elman neural network by adjusting the pitch Angle, to control the motor torque, to track the maximum power point, and expounds the control principle of the neural network control and control process.Finally, in order to verify the method of maximum power point tracking control, the use of MATLAB/SIMULINK software structures, wind power system model, the model of RBF neural network controller and Elman neural network controller to 5 mw doubly-fed wind power system simulation and control effect is verified.Simulation after generator desired speed tracking, then the ideal power output, the largest wind energy utilization coefficient were analyzed, and verified based on Elman neural network controller has obtained more ideal control effect.