Wind driven generator stability control method based on hybrid neural network

The invention relates to a wind driven generator stability control method based on a hybrid neural network, which comprises the following steps of: (1) collecting the wind speed and corresponding active power; (2) preprocessing the filtering wave; (3) debugging the GA-BP (Genetic Algorithm - Back Propagation) algorithm; (4) training the neural network; (5) calculating the result on the display screen. The method has the advantages that the accuracy is high so that the performance of the wind driven generating system can be well fitted; the computing speed is high so that the system meets the requirement of real time property; and the realization of the GA-BP neural network algorithm through programming by using a DSP (Digital Signal Processor) is effective to increase the speed of the GA-BP neural network algorithm and better exert the parallelism of the GA-BP neural network algorithm.