UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 5
May-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRCN06033


Registration ID:
215300

Page Number

198-205

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Title

Generator –Transformer Unit Fault Identification Using Backup Protection By Generalised Regression Neural Networks

Abstract

This research work describes the fault identification for the Transformer coupled with a generator unit. The reliability and functionality of protection devices are improved with the help of backup protection scheme. Magnetizing inrush, normal and over-excitations are some of the different operating system used in transformer. This research work is simulated using the PSCAD/EMTDC software with artificial neural network. The proposed research work uses the independent amplitude of the current waveform. The signal extracted from these models can be used to prepare training sets for pattern matching algorithm. Hence, Generator-Transformer unit is developed into PSCAD models for either single phase or three phase fault magnetic inrush and for no fault condition. Therefore, fault and normal operating conditions are categorized by using mho circle and current waveform at various global resistance condition. Similarly, faults and normal operating conditions classified by resilient back propagation using Generalised Regression Neural Networks (GRNN). Using electro-magnetic transient program PSCAD/EMTDC, a fragment of power system is modeled.

Key Words

backup protection scheme, PSCAD/EMTDC, Generalised Regression Neural Networks Neural Networks , fault current identification in transformer

Cite This Article

"Generator –Transformer Unit Fault Identification Using Backup Protection By Generalised Regression Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.198-205, May - 2019, Available :http://www.jetir.org/papers/JETIRCN06033.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Generator –Transformer Unit Fault Identification Using Backup Protection By Generalised Regression Neural Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp198-205, May - 2019, Available at : http://www.jetir.org/papers/JETIRCN06033.pdf

Publication Details

Published Paper ID: JETIRCN06033
Registration ID: 215300
Published In: Volume 6 | Issue 5 | Year May-2019
DOI (Digital Object Identifier):
Page No: 198-205
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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