Analysis of power quality signals using an adaptive time-frequency distribution

Abstract

Spikes frequently occur in power quality (PQ) disturbance signals due to various causes such as switching of the inductive loads and the energization of the capacitor bank. Such signals are difficult to analyze using existing time-frequency (TF) methods as these signals have two orthogonal directions in a TF plane. To address this issue, this paper proposes an adaptive TF distribution (TFD) for the analysis of PQ signals. In the proposed adaptive method, the smoothing kernel's direction is locally adapted based on the direction of energy in the joint TF domain, and hence an improved TF resolution can be obtained. Furthermore, the performance of the proposed adaptive technique in analyzing electrical PQ is thoroughly studied for both synthetic and real world electrical power signals with the help of extensive simulations. The simulation results (specially for empirical data) indicate that the adaptive TFD method achieves high energy concentration in the TF domain for signals composed of tones and spikes. Moreover, the local adaptation of the smoothing kernel in the adaptive TFD enables the extraction of TF signature of spikes from TF images, which further helps in measuring the energy of spikes in a given signal. This new measure can be used to both detect the spikes as well as to quantify the extent of distortion caused by the spikes in a given signal.