In this paper a method in intelligent monitoring of the power quality events is presented. The main objectives are the identification and classification of these events. A method for classification is used based on the combination of S-transform and neural networks. The S-transform, which is based on the wavelet transform with a phase correction, provides frequency dependent resolutions that si...

Effective identification of complex power quality disturbances (PQDs) is the premise and key to improving issues in current grid environment. However, with increasing application solid-state switches, nonlinear devices, multi-energy system generation, disturbance signals are distorted complicated. This increases difficulty PQDs identification. To address this issue, paper presents a novel metho...

The purpose of this paper is to review the state of the art techniques in signal processing for automatic classification of power quality events and to give a sign of the next trends. The time when power quality monitoring equipment just takes pictures of raw waveforms has gone. Nowadays, power quality monitoring systems are becoming able to identify and classify events automatically in order t...