A comprehensive review on soft computing and signal processing techniques in feature extraction and classification of power quality problems

Power quality (PQ) is the interface of electrical power with electrical equipment. The distribution of power supply constantly at high quality to the consumers is predicted by the electrical power systems. The enormous increase in sensitive loads, power electronic devices, nonlinear loads, and incorporation of nonconventional energy sources like solar and wind energy to the electrical power grid is one of the most important sources of PQ events. The identification of PQ events by analyzing distortion of voltage and current waveform is a very important task for power system monitoring. The expansion of novel methods to classify the PQ issues is now a most important concern. This article gives a broad review on the applications of signal processing techniques and soft computing methods used to extract the features and for optimal feature selection of PQ events. This paper helps to motivate and guide the researchers towards the solutions to a problem in the area of PQ assessment.