EMD based Detrending of Non-linear and Non-stationary Power System Signals

Abstract

In electromechanical modal analysis of power systems using Wide Area Measurement System (WAMS) based setup, signal processing is complex as the signals are non-stationary and non-linear in nature. In order to get accurate modal parameters, as a first step, it is required to remove the non-linear trend of the signal. In the literature, many conventional methods such as filtering, averaging and peak detection techniques are employed for removing trend. In this paper, Empirical Mode Decomposition (EMD) method, an iterative algorithm is presented to detrend a signal. The EMD method and its variant are compared with another popularly used peak detection method referred to as the Zhou's detrending algorithm to find the efficacy of the EMD methods. To test the algorithms, a four machine, two-area power system with three-wind farms is modeled and simulated to generate the power system signals which bring out non-linear and non-stationary nature. Further, the modal characterization is carried out employing Prony analysis. © 2021 IEEE.