High impedance faults detection using artificial neural network

T. M. Lai, L. A. Snider, E. Lo, C. H. Cheung, K. W. Chan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 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 languageEnglish
Title of host publicationSixth International Conference on Advances in Power System Control, Operation and Management - Proceedings
PublisherInstitute of Electrical Engineers
Pages821-826
Number of pages6
ISBN (Print)0863413285, 9780863413285
DOIs
Publication statusPublished - 2003
Externally publishedYes
EventSixth International Conference on Advances in Power System Control, Operation and Management - Proceedings - Hong Kong, China
Duration: 11 Nov 200314 Nov 2003

Publication series

NameSixth International Conference on Advances in Power System Control, Operation and Management - Proceedings
Volume2

Conference

ConferenceSixth International Conference on Advances in Power System Control, Operation and Management - Proceedings
Country/TerritoryChina
CityHong Kong
Period11/11/0314/11/03

Keywords

  • Finite Impulse Response Filter Bank
  • High Impedance Faults
  • Neural Network

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