Research on a novel passive islanding detection method

Abstract

In distributed generation systems, islanding detection is a necessary function of grid-connected inverters. In view of the performance disadvantages of traditional passive and active islanding detection methods, this paper proposes a novel passive islanding detection method. The proposed method first extracts characteristic parameters from the inverter output voltage signal and inverter output current signal through lifting wavelet transform, and then conducts the pattern recognition of these extracted characteristic parameters via BP neural network, so as to judge if there is an islanding phenomenon. As verified by the simulation and experiment results, the islanding detection method proposed in this paper is effective, and is featured by high detection speed and small non-detection zone, without affecting electric energy quality; its detection performance has been remarkably improved in comparison with that of traditional islanding detection methods.