Real Time Power Quality Monitoring Using Discrete Wavelet Transform

Abstract

The revolution of renewable energy resources (RES) lead to a significant increase in using power electronics devices which have increased the power quality (PQ) issues. Poor PQ causes several problems such as; misoperation of the equipment, loss of important data, protection devices misoperation, and overheating. The mitigation of PQ disturbances can be easily done only if these disturbances are well detected and classified. Traditional detection techniques have some shortages in case of power system signals which are non-stationary and have transients. Unlike Fourier transform (FT) a discrete wavelet transform (DWT) multi-resolution analysis (MRA) is used to deal with the PQ disturbances in order to accurately detect, localize, and classify these events. In this research, an attempt will be made to design a real time system for monitoring the PQ, to detect and classify PQ disturbances using DWT; specifically voltage sag, swell, and interruption. The proposed system has been simulated and built using National Instruments compact RIO controller (NI-cRIO 9063) and the monitoring has been done using laboratory virtual instrument engineering workbench (LabVIEW). Utilizing the high speed acquisition of the cRIO based system using field-programmable gate array (FPGA) and real time, results in a significant accuracy in detection and classification of the PQ events in terms of magnitude and time (Sag/ Undervoltage, Swell/ Overvoltage, and Interruption/ Sustained Interruption). Connecting the proposed system with the grid shows very high speed and accuracy in grid monitoring.