Open AccessResearch on a novel passive islanding detection method
Author(s) -
Dong Xie,
Dajin Zang,
Peng Gao,
Junjia Wang,
Zhu Zhu
Publication year - 2021
Publication title -
indian journal of power and river valley development
Language(s) - English
Resource type - Journals
ISSN - 0019-5537
DOI - 10.18311/ijprvd/2021/28068
Subject(s) - islanding , inverter , computer science , voltage , signal (programming language) , grid , electronic engineering , energy (signal processing) , wavelet transform , artificial neural network , wavelet , distributed generation , control theory (sociology) , engineering , artificial intelligence , electrical engineering , mathematics , renewable energy , geometry , statistics , control (management) , programming language
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.