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115397

Recurrent Neural Networks Based Fault Detection for Synchronous Generator Stator Windings Protection.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Electronics and Communications Engineering

Abstract

This paper presents a proposed approach for fault detection and faulty phase(s) identification for synchronous generator protection-based om artificial neural networks. In order to perform this approach: the protection system is subdivided into different neural network modules for fault detection and classification. The proposed approach uses Recurrent Neural Network (RNN) to detect and classify the synchronous generator internal faults. The RNN uses the three-phase current measurements from both sides of the synchronous generator stator winding as its input data. RNN was trained using various sets of data available from the simulation results of the selected synchronous model under different fault scenarios (fault type, fault location, fault resistance and fault inception angle). Simulation results of the proposed RNN based synchronous generator stator winding protection provide a great performance; in terms of accuracy, speed and reliability.

DOI

10.21608/bfemu.2020.115397

Keywords

Synchronous generator, differential protection, Recurrent neural networks, Fault Detection, Fault classification

Authors

First Name

A.

Last Name

Helal

MiddleName

-

Affiliation

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

Email

-

City

-

Orcid

-

First Name

H.

Last Name

El Dessouki

MiddleName

-

Affiliation

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

Email

-

City

-

Orcid

-

First Name

A.

Last Name

Hatata

MiddleName

-

Affiliation

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

Email

-

City

-

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

Mohamed Abd El-Moneim

Last Name

Tantawy

MiddleName

Mohamed

Affiliation

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

Email

-

City

Mansoura

Orcid

-

Volume

38

Article Issue

1

Related Issue

15576

Issue Date

2013-03-01

Receive Date

2013-01-17

Publish Date

2020-09-26

Page Start

1

Page End

13

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 38_Issue 1_Pages 1-13.pdf

PDF . 18.0MB

Link

https://bfemu.journals.ekb.eg/article_115397.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=115397

Order

6

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