An Innovative Single Shot Power Quality Disturbance Detector Algorithm

Power Quality Disturbances (PQD) have affected many people due to the growing number of electronic nonlinear loads and because significant increase renewable sources connected grid. Previous works shown development algorithms detect classify these disturbances. A thorough review PQD detector pointed out use machine learning deep as most used, accurate up-to-date approaches deal with this problem. Up until now, were used in a sliding window manner that often fail identify more than one disturbance single frame. In work, an innovative architecture called Single Shot Disturbance Detection (SSPQDD) has been developed solve Several experiments conducted using simulation dataset order validate performances proposed SSPQDD comparison other available literature terms computational resources, accuracy identification layers. Furthermore, experimental testbench carried test real measurement data case multiple disturbances The overall obtained was 96.55% detection.