Mother wavelet selection method for voltage sag characterization and detection

Abstract

Wavelet-based techniques are strongly recommended as a good alternative for the fast detection and characterization of voltage sags. However, the accuracy and effectiveness of these techniques greatly depend on selecting an appropriate mother wavelet. Therefore, in this work, a wavelet correlation-based technique has been developed to select the most appropriate mother wavelet for the characterization and detection of voltage sag. The efficacy and accuracy of the proposed method are tested with twenty different mother wavelets on various voltage sag signals, namely, recorded industrial, multi-stage, and synthetic signals under different conditions of unbalanced. It is shown that the mother wavelet having the highest similarity with a voltage sag provides the best results for its characterization and detection. Further, the various performance parameters of voltage sags, namely magnitude, duration, sag initiation, recovery, are evaluated with the proposed method and results are compared with Independent Component Analysis (ICA), hybrid wavelet, dq-transformation, Enhanced Phase Locked Loop (EPLL), Fast Fourier Transform (FFT) methods showing that the performance of the proposed method is better than other existing methods for sag detection. In addition, the proposed method can also be used for estimating the magnitude of voltage sags.