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M.Tech / M.E / PhD Thesis | Electrical Engineering | India | Volume 5 Issue 5, May 2016

Identification of Type & Location of a Fault in a Distributed Generation System Using Neural Network

Saurabh Awasthi | Ranjay Singh

Abstract: Distributed generation system offers several distinguish advantages over conventional centralized generation system. However protection scheme of such system has always been a challenge as it can leads to numerous unwanted situation such as reclosing failure. This paper proposes a Neural Network based method to identify the location and type of a particular fault that may occur in a distribution network operated with Distributed generation system. A distributed network with DG has been considered for data generation and based upon the data so collected in terms of sample of Voltage and current, after simulation, training, testing and validation of Neural Network is carried out. In the event of any fault within the system the trained neural network identify its type and location on account of the pattern recorded earlier.

Keywords: Distributed Generation, Renewable Energy systems, Neural Network, Simulation, Distribution Network

Edition: Volume 5 Issue 5, May 2016,

Pages: 2059 - 2065