Determining Five Kinds of Power Quality Disturbances by Using Statistical Methods and Wavelet Energy Coefficients

Abstract

In this paper, it is tried to compare two methods for determining pure sine and five kinds of power quality disturbances (PQD) such as voltage sag, voltage swell, voltage with harmonics, transients and flicker. These methods are statistical methods and wavelet based effective feature extraction method. Before classifying power quality signals, one of the feature extraction method must be applied. So, these two methods are compared. Firstly, statistical methods are applied to PQD. It is observed that if PQD signal is created at the zero crossing points of the voltage signal, statistical methods give satisfactory result. But occurrence of disturbances at these points is not guaranteed in real systems. It is seen that first method may confuse some PQD according to occurrence place of disturbances. So second method is used for extracting the energy distribution features of PQD constituted in eight different points (00, 450, 900, 1350, 1800, 2250, 2700, 3150). Parseval’s theorem and multi-resolution analysis (MRA) technique of discrete wavelet technique (DWT) are used. It is observed that this method gives satisfactory results for eight different points. © 2017, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.