A hybrid islanding detection technique for inverter based distributed generations

This paper proposes a new hybrid islanding detection method for grid-connected inverter based distributed generation units. The proposed method combines passive and active islanding detection techniques to aggregate their individual advantages and reduce or eliminate their drawbacks. The passive method is based on extraction of critical system parameters from local voltage measurements at target DG location and application of decision tree based classifiers for extraction of decision rules in order to detect islanding events. The active method is based on Sandia Frequency Shift technique and is initiated only when the passive method is unable to properly classify between islanding and other transient generating events, thus minimizing the power quality degradation introduced in the system. A detailed case study on a grid-connected PV system is performed to evaluate the performance of the proposed technique. Test results demonstrate the effectiveness of the proposed method in detection of islanding events in grid-connected distributed generations.