Determination of the power quality event types with an intelligent recognition system

In this work, an intelligent recognition system is developed to determine the type of power quality events which cause power quality problems. Three phase voltage signals are used to determine the types of power quality events. In the first step of this recognition system, normalization and segmentation processes are applied to the three phase voltage signals. In the second step, wavelet transform method is applied to the voltage signals and wavelet transform coefficients are obtained. Later, the two phase feature extraction process is applied to these coefficients and an effective feature vector which stands for the distinctive features of voltage signals and reduces the data size. In the last step of the intelligent recognition system, power quality event types are determined by using an artificial neural network classifier Simulation data obtained from the ATP/EMTP model are used to evaluate the performance of the developed system. According to the results, the recognition system is classified the three phase event types very accurately.