Power quality disturbances detection and location using mathematical morphology and complex wavelet transformation

Abstract

Based on mathematical morphology (MM) and complex wavelet, a novel method on power quality (PQ) disturbance detection and location is presented in this paper. At first, a generalized morphology filter with horizontal linear structure elements is designed to filter impulses and random white noises in PQ disturbance signals. Numerical simulation results show that the characteristics of the original signal can be well retained and the noise interferences are suppressed effectively with the proposed filter method. Then, to the filtered results, the complex wavelet derived by Daubechies real wavelet and its compound information are applied to detect and locate the start and end time that the disturbance occurs. The voltage interruption, voltage sag, voltage swell, high frequency oscillation and harmonic distortion are used to verify the validity of the filter-location approach. Simulation results show the integrated detection approach of morphology-complex wavelet is valid and effective. Besides, it can reduce calculation time and can be implemented easily in the available hardware.