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122340

Neural Network Based Fault Detector and Classifier for Synchronous Generator Stator Windings.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Electrical Engineering

Abstract

This paper presents an application of multilayer feedforward neural network (MFNN) as a differential protection for synchronous generators. Two MFNN are designed, trained, and tested in this paper. The first one has two outputs which detect the internal and external fault state. The other neural network has four outputs to classify the faulty phases. The proposed neural fault detector and classifier were trained using various sets of data available from a selected synchronous model and simulating different fault scenarios (fault type, fault location, fault resistance and fault inception angle). The results show very good behavior of the MFNN and it was more reliable and accurate than conventional methods. It shows that MFNN offer the possibility to be used for on line synchronous generator protection and give satisfactory results. 

DOI

10.21608/bfemu.2020.122340

Keywords

differential protection, Generator protection, Multilayer feedforward neural networks, Fault detector and classification

Authors

First Name

Ahmad

Last Name

Hatata

MiddleName

-

Affiliation

Electrical Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.

Email

-

City

Mansoura

Orcid

-

First Name

Ahmed

Last Name

Helal

MiddleName

-

Affiliation

Assistant Professor., Electrical and Control Engineering Department., Faculty of Engineering., Arab Academy for Science and Technology., Alex., Egypt.

Email

-

City

Alexandria

Orcid

-

First Name

Hesien

Last Name

El Dessouki

MiddleName

-

Affiliation

Dept of Elec. Engineering and Control, Faculty of Engineering, Arab Academy for Science and Technology, Alex. Egypt.

Email

-

City

Alexandria

Orcid

-

First Name

Magdi

Last Name

El-Saadawi

MiddleName

Mohamed Ali

Affiliation

Professor of Electrical Engineering Department., Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.

Email

m_saadawi@mans.edu.eg

City

Mansoura

Orcid

-

First Name

Mohammed

Last Name

Tantawy

MiddleName

-

Affiliation

Professor of Electrical Engineering Department, Faculty of Engineering., El-Mansoura University., Mansoura., Egypt.

Email

-

City

Mansoura

Orcid

-

Volume

36

Article Issue

4

Related Issue

17858

Issue Date

2011-12-01

Receive Date

2011-08-11

Publish Date

2020-11-09

Page Start

19

Page End

28

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 36_Issue 4_Pages 19-28.pdf

PDF . 14.7MB

Link

https://bfemu.journals.ekb.eg/article_122340.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=122340

Order

13

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