A novel voltage sag detection method for analyzing charging quality of electric vehicle

Abstract

Electric car charging quality is severely impacted by voltage sag in the distribution network. Voltage sag events frequently occur in conjunction with other power quality disturbances, which leads to signal waveform distortion, making it difficult to identify voltage sag characteristics in composite power quality disturbance signals. The voltage sag amplitude, phase angle jump, and duration are all accurately detected in the composite power quality disturbance signal thanks to the method's two-stage waveform decomposition model, which eliminates the interference of the transition segment by pinpointing the beginning and ending points of the voltage sag using DQ transform. Moreover, the designed simulation experiments further verify that our proposed method outperforms other mainstream approaches, and it can be well used to effectively detect voltage sags of different causes under various signals that disturb the composite power quality, with an average accuracy rate of over 98.86 %.