FAULT CLASSIFICATION AND LOCATION TECHNIQUES FOR TRANSMISSION LINES IEEE SYSTEM

FAULT CLASSIFICATION AND LOCATION TECHNIQUES FOR TRANSMISSION LINES IEEE SYSTEM

Registration ID: IJNRD_224279

Published ID: IJNRD2406437

DOI: Click Here to Get

Mr. Gaurav G. feran , Mr. C.M. Bobade

It is imperative to safeguard the transmission line against the unavoidable effects of defects, hence intelligent schemes for fault detection and classification must be implemented immediately. This article presents the use of artificial neural networks (ANN) to detect, identify, and classify faults on transmission lines with better zone reach settings. The inputs to the artificial neural network (ANN) are defined as the fundamental voltage and current magnitudes as determined by the Discrete Fourier Transform (DFT). Section 2, the most important area that needs to be secured, is where the relay is located. A variety of fault datasets, which were derived from the MATLAB simulation of several fault scenarios, including different types of faults at variable fault inception angles, fault locations, and fault resistances, were used to train and test the ANN. The simulation outcomes illustrated that the entire shunt faults including forward and reverse fault, it’s section and phase can be accurately identified within a half cycle time. The advantage of this scheme is to provide a major protection up to 99.5% of total line length using single end data and furthermore backup protection to the forward and reverse line sections. This routine protection system is properly discriminatory, rapid, robust, enormously reliable and incredibly responsive to isolate targeted fault.

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"FAULT CLASSIFICATION AND LOCATION TECHNIQUES FOR TRANSMISSION LINES IEEE SYSTEM", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 6, page no.e397-e404, June-2024, Available :https://ijnrd.org/papers/IJNRD2406437.pdf

Volume 9 Issue 6, June-2024

Pages : e397-e404

Paper Reg. ID: IJNRD_224279

Published Paper Id: IJNRD2406437

Downloads: 000121114

Research Area: Electrical Engineering 

Country: amravati, maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2406437.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2406437

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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