Model for Analysis of Power Quality Index and Determination of Its Causes and Effects

Abstract

The Power Quality (PQ) gets affected not only because of the load but also because of the source as power electronics devices applications are widely spread in both sides. The renewable energy sources used power electronics converters and the nonlinear loads connected at consumer premises are the main causes of PQ distortions. This hampered PQ supply, when fed to equipments (or loads), affect the performance of them by increasing the energy lose, increasing the electricity bill and reducing their life expectancy. This article proposed a model for the analysis of different PQ events by means of Wavelet Transforms (WT) and Artificial Neural Network (ANN) composition. The different types of PQ events are generated in the laboratory under the source and load distortion conditions. The supply side voltage waveforms under linear load condition and load side current waveforms under normal supply conditions are considered for analysis. These waveforms are processed by WT and the scaling coefficients are determined for various PQ events. These coefficients are used to train ANNs for decision making. The proposed model is developed in MATLAB for offline and online applications. The results obtained by both the methods are compared and found satisfactory. At the end, the losses incurred in the transformer considered for performance, its efficiency and life expectancy are presented for different PQ conditions.