Islanding detection in a distribution network with distributed generators using signal processing techniques

Seong-Cheol Kim, Papia Ray, Surender Reddy Salkuti


This paper proposes quick & accurate islanding detection technique for a distribution system with distributed generators (DGs). Here two schemes of islanding detection based on signal processing is proposed of which one is based on discrete wavelet transform (DWT) with artificial neural network (ANN), and another one is based on S-transform with ANN. The negative sequence current/voltage signals are retrieved at targeted DG location which are used for islanding detection in the distribution system. Here, the wavelet and S-transforms are used for fault location and classification applications. Further, the feature extraction is used for reducing the size of data matrix by transforming it into set of features. In this work, particle swarm optimization (PSO) based feature selection scheme is applied. Simulation results on test system indicate the efficacy of proposed islanding detection techniques.

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Copyright (c) 2020 Seong-Cheol Kim, Papia Ray, Surender Reddy Salkuti

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