Detection and location of power quality disturbances based on mathematical morphology and hilbert-huang transform

Abstract

With the power system development, the application of non-linear power components is becoming more and more extensive, and the power quality situation of power system has become increasingly severe. This paper proposes a novel method based on mathematical morphology (MM) and Hilbert-Huang transform (HHT), which is used to detect and analyze power quality disturbances. To effectively suppress noises, the traditional (Maragos) mathematical morphological filter is improved, so the main characteristics of original signal are reserved. And, the de-noising signal is processed by empirical mode decomposition (EMD) to obtain a set of intrinsic mode function (IMF) components. Then, using Hilbert transform to every IMF component, the instantaneous amplitude and frequency of the components can be accurately computed. Simulation results show that this method is feasible and effective and can accurately determine time, amplitude and frequency of the power quality disturbances.