Detection and classification of power quality disturbances based on wavelet packet decomposition and support vector machines

This paper proposes a novel method based on wavelet packet decomposition and support vector machines for detection and classification of power quality disturbances. Wavelet packet decomposition is mainly used to extract features of power quality disturbances; and support vector machines are mainly used to construct a multi-class classifier which can classify power quality disturbances according to the extracted features. The topology structure of the proposed method and the multi-class support vector machine classification tree are both shown in this paper. Results of simulation and analysis demonstrate that the proposed method can achieve higher correct identification rate, better convergence property and less training time compared with the method based on artificial neural network. Therefore, through this method power quality disturbances can be detected and classified effectively, accurately and reliably.