Recognition and classification of power quality disturbances based on complex wavelet transform and neural network

In order to solve the problem of the power quality disturbances in real-time monitoring and automatic identification, this paper proposes a identification and classification method of power quality disturbances based on complex wavelet transform and artificial neural networks. For extracting the eigenvector of the dynamic power quality disturbances, Db4 orthogonal compact support complex wavelet of complex wavelet transform is used. According to the extracted eigenvector, the dynamic power quality disturbances are identified and classified through neural network. Simulation and test results show that the method is correct and effective, and has a high rate of correct identification.