A hybrid framework for fault detection, classification, and location-Part I: Concept, structure, and methodology

Joe Air Jiang, Cheng Long Chuang, Yung Chung Wang, Chih Hung Hung, Jiing Yi Wang, Chien Hsing Lee, Ying Tung Hsiao

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)

Abstract

Bridging the gap between the theoretical modeling and the practical implementation is always essential for fault detection, classification, and location methods in a power transmission-line network. In this paper, a novel hybrid framework that is able to rapidly detect and locate a fault on power transmission lines is presented. The proposed algorithm presents a fault discrimination method based on the three-phase current and voltage waveforms measured when fault events occur in the power transmission-line network. Negative-sequence components of the three-phase current and voltage quantities are applied to achieve fast online fault detection. Subsequently, the fault detection method triggers the fault classification and fault-location methods to become active. A variety of methodsincluding multilevel wavelet transform, principal component analysis, support vector machines, and adaptive structure neural networksare incorporated into the framework to identify fault type and location at the same time. This paper lays out the fundamental concept of the proposed framework and introduces the methodology of the analytical techniques, a pattern-recognition approach via neural networks and a joint decision-making mechanism. Using a well-trained framework, the tasks of fault detection, classification, and location are accomplished in 1.28 cycles, significantly shorter than the critical fault clearing time.

Original languageEnglish
Article number5771142
Pages (from-to)1988-1998
Number of pages11
JournalIEEE Transactions on Power Delivery
Volume26
Issue number3
DOIs
Publication statusPublished - 2011 Jul 1

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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