Application Of Wavelet Transform To Detect Power Quality Transient Signal

With the wide application of electric & electronic devices in power system, powerquality problems have already become the focus which both suppliers and users of electricityhave paid close attention to. In order to improve the power efficiency, it is necessary to detectthe power quality quickly, classify them accurately and deal with them effectively.Due to the non-steady characteristic of power quality transient, the processing method ofwavelet transform is adopted. The technique of wavelet transform is good for detecting,localizing and analyzing power quality disturbance signals. However, as the signals underanalysis are always disturbed by noises, the effect of the WT technique is degraded. Strongnoises even lead to a wrong judgement. Several kinds of threshold denoising methods arecompared in this paper. The experiment proves that the denoising effect is not ideal if usingthe threshold method alone. By using the denoising method based on the combination of thewavelet transform correlativity and soft-threshold, the noise and unnecessary information iseliminated and the preceding problem is solved.To the power quality transient disturbance classification, the signals are decomposed withwavelet multi-resolution analysis and the feature vectors are extracted through the coefficientsat different levels, and then the power quality disturbance classification can be achieved. Testresults show that this approach is effective to classify power quality transient signals. Thereby,aiming at power quality transient disturbance, it is easy to take corresponding measure toimprove power quality.