Improvement of wavelet based methods for classification of power quality disturbances

In this paper an improvement of wavelet based methods for detection and classification of power quality disturbances is presented. In the feature extraction process wavelet analysis is also used as in the comparing methods. However, the feature vector is extended with three other coefficients in order to improve the accuracy of the algorithm. In order to evaluate the proposed method, large number of experiments is performed, using SVM (Support Vector Machines) as a classification method. The obtained classification accuracy is higher than 98%.