Estimation of Single-Phase and Three-Phase Power-Quality Indices Using Empirical Wavelet Transform


Application of an empirical wavelet rework (EWT)-primarily based time-frequency technique is proposed in this paper for the estimation of power-quality indices (PQIs). This system 1st estimates the frequency parts present in the distorted signal, computes the boundaries, and then filtering is done based mostly on the boundaries computed. This method is effective and offers many benefits over alternative techniques as a result of the scaling function and wavelets adapt themselves consistent with the information contained in the signal and no previous info regarding the signal is required. Besides this, the benefits of the discrete wavelet transform (DWT), wavelet packet transform (WPT), short-time Fourier transform (STFT), windowing techniques, and filter bank techniques also hold. Simulated and experimental test signals with power-quality disturbances have been analyzed and therefore the effectiveness of this technique has been shown by comparing the PQIs estimated by using the proposed method with those obtained using the DWT and WPT. The results make sure that the EWT efficiently extracts the mono component signals from the particular distorted signal and thereby accurately estimates the PQIs.

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