Power Quality Classification Scheme For A Grid-Integrated Power Distribution System

The energy trajectory has evolved over the years with the inclusion of distributed generation based on renewable energy (RE) technologies on the power system grid. The inclusion of RE technologies improves the power availability and security. However, there are serious technical concern which include voltage and frequency variation. In this paper, a power quality (PQ) classification scheme for a power distribution grid-integrated system with (RE) technologies is proposed. The proposed scheme uses the wavelet packet transform (WPT) for signal processing and feature extraction, and support vector machine (SVM) is used for PQ events classification. The proposed scheme was implemented using the WEKA machine learning platform. Furthermore, the neural network (NN) and naïve bayes (NB) classification techniques ware also tested to validate the proposed technique.