Power Quality Disturbance Localization Using Maximal Overlap Discrete Wavelet Transform

Abstract

In recent times, the wavelet-based methodologies have been developed as suitable alternatives for the real-time analysis of power system. In this paper the time-series based maximal overlap discrete wavelet transform (MODWT) technique has been proposed for the detection and the localization of different PQ disturbances. The performance of the MODWT has been compared with the traditional discrete wavelet transform (DWT). Ten different types of PQ disturbances of the voltage signal such as sag, swell, interruption, harmonic, sag with harmonics and swell with harmonics, spike, notch etc. are analyzed with the two different types of wavelet transform (WT). Each signal is decomposed up to fourth level by applying both the DWT and the MODWT. However, the MODWT is appropriate for the realtime detection of PQ disturbances as it has an ability for the free selection of the initial point of the time series. Similarly, MODWT is can apply on signal of any sample size.