Comparative Analysis between Dynamic Voltage Restorer and PWM-Switched Autotransformer in Voltage Sag Mitigation

Abstract

This research aims to address the problem of voltage sag, which is a significant power quality issue in power systems. Voltage sag can lead to power transmission and distribution line tripping and cause damage to electrical equipment. Various voltage sag mitigation devices have been developed to reduce the impact of voltage sag. In this study, we analyze the effectiveness of three types of voltage sag mitigation devices under different voltage sag conditions: three-phase fault, multi-phase fault, and energizing transformer inrush current. The three types of mitigations analyzed are Dynamic Voltage Restorer (DVR) with Park's transformation, DVR with Artificial Neural Network (ANN) controller, and PWM-switched autotransformer with Proportional-Integral (PI) controller. The simulation results using MATLAB demonstrate that all voltage sag conditions have been mitigated except for PWM-switched autotransformer during voltage sag caused by energizing transformer inrush current due to limitations of the PI controller scheme. Based on the analysis of input and output voltage waveforms, three-phase voltage magnitude before and after mitigation, and Total Harmonic Distortion (THD) value after mitigation, DVR with ANN controller is identified as the most effective voltage sag mitigation device, followed by DVR with Park's transformation and PWM-switched autotransformer.