High impedance faults detection using artificial neural network

T. M. Lai; L. A. Snider; Wai Chau Edward Lo; C. H. Cheung; K. W. Chan

High impedance faults detection using artificial neural network

T. M. Lai, L. A. Snider, Wai Chau Edward Lo, C. H. Cheung, K. W. Chan

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

13 Citations (Scopus)

Abstract

High impedance faults (HIF) are faults which are difficult to be detected by overcurrent protection relays. This paper presents a practical pattern recognition based relay algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using Finite Impulse Response (FIR) filter bank yields three-phase voltage and current in the low frequency range which fed to a classifier for pattern recognition. The classifier is based on the algorithm using neural network approach. A HIF model was also developed, where the random nature of the arc was simulated using MATLAB.

Original language	English
Title of host publication	Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings
Pages	821-826
Number of pages	6
Volume	2
Publication status	Published - 1 Dec 2003
Event	Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings - Hong Kong, Hong Kong Duration: 11 Nov 2003 → 14 Nov 2003

Conference

Conference	Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings
Country/Territory	Hong Kong
City	Hong Kong
Period	11/11/03 → 14/11/03

Keywords

Finite Impulse Response Filter Bank
High Impedance Faults
Neural Network

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{56f6e01e52564014b7cb1e2cdca99db1,

title = "High impedance faults detection using artificial neural network",

abstract = "High impedance faults (HIF) are faults which are difficult to be detected by overcurrent protection relays. This paper presents a practical pattern recognition based relay algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using Finite Impulse Response (FIR) filter bank yields three-phase voltage and current in the low frequency range which fed to a classifier for pattern recognition. The classifier is based on the algorithm using neural network approach. A HIF model was also developed, where the random nature of the arc was simulated using MATLAB.",

keywords = "Finite Impulse Response Filter Bank, High Impedance Faults, Neural Network",

author = "Lai, {T. M.} and Snider, {L. A.} and Lo, {Wai Chau Edward} and Cheung, {C. H.} and Chan, {K. W.}",

year = "2003",

month = dec,

day = "1",

language = "English",

isbn = "0863413285",

volume = "2",

pages = "821--826",

booktitle = "Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings",

note = "Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings ; Conference date: 11-11-2003 Through 14-11-2003",

}

Lai, TM, Snider, LA, Lo, WCE, Cheung, CH & Chan, KW 2003, High impedance faults detection using artificial neural network. in Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings. vol. 2, pp. 821-826, Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings, Hong Kong, Hong Kong, 11/11/03.

High impedance faults detection using artificial neural network. / Lai, T. M.; Snider, L. A.; Lo, Wai Chau Edward et al.
Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings. Vol. 2 2003. p. 821-826.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - High impedance faults detection using artificial neural network

AU - Lai, T. M.

AU - Snider, L. A.

AU - Lo, Wai Chau Edward

AU - Cheung, C. H.

AU - Chan, K. W.

PY - 2003/12/1

Y1 - 2003/12/1

N2 - High impedance faults (HIF) are faults which are difficult to be detected by overcurrent protection relays. This paper presents a practical pattern recognition based relay algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using Finite Impulse Response (FIR) filter bank yields three-phase voltage and current in the low frequency range which fed to a classifier for pattern recognition. The classifier is based on the algorithm using neural network approach. A HIF model was also developed, where the random nature of the arc was simulated using MATLAB.

AB - High impedance faults (HIF) are faults which are difficult to be detected by overcurrent protection relays. This paper presents a practical pattern recognition based relay algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using Finite Impulse Response (FIR) filter bank yields three-phase voltage and current in the low frequency range which fed to a classifier for pattern recognition. The classifier is based on the algorithm using neural network approach. A HIF model was also developed, where the random nature of the arc was simulated using MATLAB.

KW - Finite Impulse Response Filter Bank

KW - High Impedance Faults

KW - Neural Network

UR - http://www.scopus.com/inward/record.url?scp=4344654713&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 0863413285

SN - 9780863413285

VL - 2

SP - 821

EP - 826

BT - Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings

T2 - Sixth International Conference on Advances in Power System Control, Operation and Management - Proceedings

Y2 - 11 November 2003 through 14 November 2003

ER -

High impedance faults detection using artificial neural network

Abstract

Conference

Keywords

ASJC Scopus subject areas

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