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A Machine Intelligence Approach for Classification of Power Quality Disturbances

This paper presents the combination of advanced signal processing techniques and the machine intelligence approach to classify the power quality events. The Wavelet Transform (WT) and the S – Transform (ST) are utilized to extract the important useful features of the disturbance signal. The features extracted by using the above approaches are used to train a PNN classifier for automatic classification of the PQ disturbances. Eleven types of power quality disturbances are considered for the classification purpose. The simulation results show that the combination of S-Transform and PNN is an effective method to detect and classify different power quality disturbances.