Visualizing time-varying power quality indices using generalized empirical wavelet transform

Tracking of instantaneous power quality (PQ) indices is very essential for better characterization of the time-varying voltage and current signals. This paper presents the estimation of time-varying PQ indices for accurate interpretation of disturbances using a generalized empirical wavelet transform (GEWT). This approach is based on adaptive segmentation of Fourier spectrum and followed by an appropriate filter design to extract the individual frequency components. The main emphasis of this work is to estimate the actual frequencies present in the signal by overcoming the problem of spectral leakage. A preliminary investigation of time domain amplitude variation of the signal helps in realizing the presence of low-frequency interharmonics and thereby permitting to extract the fundamental frequency component perfectly. Hence, the GEWT is employed to assess successfully all sorts of power signals having disturbances such as voltage fluctuation, sag, swell, interruption, transients, harmonics, and interharmonics. The robustness and applicability of the GEWT for PQ analysis have been verified by analyzing several distorted signals generated using PSCAD, recorded waveforms available in IEEE database and a few real signals. Finally, the estimated GEWT-based time-varying single phase PQ indices are compared with the indices obtained from IEC defined fast Fourier transform (FFT) and fast S-transform (FST).