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131853

On-line Fault Detection of Transmission Line Using Artificial Neural Network.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Computer Engineering and Systems

Abstract

 As the voltage and current waveforms arc deformed due to transient during faults, their patient changes according to the type of fault. The Artificial Neural Network (ANN) c2 then be used for fault detection due to its distinguished behavior in pattern recognition. In order to minimize the structure and timing of the ANN, preprocessing of the voltage and current waveforms was done, The data delivered from a simulated power system using PSCAD (EMTP with cad system) was used for training and testing the ANN. An experimental setup, consists of a 3 phase power supply module and transmission line module, is utilized. A set of signal conditioning circuits is designed and implemented in order to transfer data to a PC which is used as an on-line relay for fault detection. This is done via a data acquisition card (CIO DAS1602/12). The Matlab program captures and processes real data for training the ANN. Applying different types of saults for testing the system, right tripping action was taken and the type of fault was correctly identified. The suggested artificial neural network algorithm has been found simple and effective hence could be implemented in practical application.

DOI

10.21608/bfemu.2020.131853

Authors

First Name

Samah

Last Name

El Safty

MiddleName

M.

Affiliation

Faculty of Engineering, Arab Academy for Science and Technology, Alexandria, Egypt

Email

-

City

Alexandria

Orcid

-

First Name

Hamdy

Last Name

Ashour

MiddleName

A.

Affiliation

Faculty of Engineering, Arab Academy for Science and Technology, Alexandria, Egypt

Email

-

City

Alexandria

Orcid

-

First Name

Hesien

Last Name

El Dessouki

MiddleName

-

Affiliation

Faculty of Engineering, Arab Academy for Science and Technology, Alexandria, Egypt

Email

-

City

Alexandria

Orcid

-

First Name

Mohamed

Last Name

El Sawaf

MiddleName

-

Affiliation

Faculty of Engineering, Arab Academy for Science and Technology, Alexandria, Egypt

Email

-

City

Alexandria

Orcid

-

Volume

30

Article Issue

4

Related Issue

19437

Issue Date

2005-12-01

Receive Date

2005-10-11

Publish Date

2020-12-23

Page Start

16

Page End

21

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 30_Issue 4_Pages 16-21.pdf

PDF . 101.2kB

Link

https://bfemu.journals.ekb.eg/article_131853.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=131853

Order

29

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023