Application research of wavelet neural network and PID in maximum power point tracking of wind power system

In view of problem that power coefficient must keep maximum value when wind power system is in underpower stage, the paper proposed a control strategy of maximum power point tracking based on wavelet neural network and PID controller. The strategy uses wavelet neural network to make online identification for power coefficient and returns sensitivity information after ending of one identification period. PID controller adjusts PID parameters according to the sensitivity information. Simulation result shows that wavelet neural network and PID controller improves blade top speed ratio, power coefficient and output power of wind power system and reduces response time compared with common PID controller, which realizes optimal running of wind turbines.