Investigation on the effectiveness of classifying the voltage sag using support vector machine

Voltage sags are currently one of the vital issues in power quality today. Voltage sag is a short duration reductions in RMS voltage caused by fault, induction motor starting and transformer energizing. Aim of this paper is to classify the caused of sag either by fault or induction motor starting using SVM. In this paper, the voltage sag was analyzed using PSCAD model. Then, a method to identify voltage sag using mother wavelet Daubechies 4 and support vector machines are used. The waves were discomposed into 10 levels using wavelet transform, afterwards, the selected energy features that were extracted from different levels, were employed as the inputs of the Support Vector Machines to classify the voltage sag.