Power quality disturbance automatic recognition based on wavelet and genetic network

Based on a wavelet transform, neural network and evolution network a novel approach to detect and classify various types of electric power quality disturbances is presented in this paper. At first the Daubechies3 wavelet is applied to decompose the signals containing disturbances, and the feature vectors are extracted through the wavelet coefficients with five scales. Then disturbance types are identified through the pattern recognition classifier based on a neural network and genetic algorithm. Numerical results show that the proposed method has good performance in speed, convergence and accuracy.