Evaluation and classification of power quality disturbances based on discrete Wavelet Transform and artificial neural networks (original) (raw)

In this paper, detection method and classification technique of power quality disturbances is presented. Due to the increase of nonlinear load recently, it becomes an essential requirement to insure high level of power supply and efficient commotional consuming. Wavelet Transform represents a powerful mathematical platform which is needed especially at non-stationary situations. Disturbances are fed into wavelets to filter, detect and extract its features at different frequencies. Training of features extracted by WT is done using artificial neural networks ANN to classify power quality disturbances.