Power System Distributed On-line Fault Section Estimation Using Decision Tree Based Neural Nets Approach

Hong-Tzer Yang, Wen Yeau Chang, Ching Lien Huang

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

This paper proposes a distributed neural nets decision approach to on-line estimation of the fault section of a transmission and distribution (T&D) system. The distributed processing alleviates the burden of communication between the control center and local substations, and increases the reliability and flexibility of the diagnosis system. Besides, by using the algorithms of data-driven decision tree induction and direct mapping from the decision tree into neural net, the proposed diagnosis system features parallel processing and easy implementation, overcoming the limitations of overly large and complex system. The approach has been practically tested on a typical Taiwan Power (Taipower) T&D system. The feasibility of such a diagnosis system is presented.

Original languageEnglish
Pages (from-to)540-546
Number of pages7
JournalIEEE Transactions on Power Delivery
Volume10
Issue number1
DOIs
Publication statusPublished - 1995 Jan 1

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Decision trees
Neural networks
Processing
Large scale systems
Communication

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

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Power System Distributed On-line Fault Section Estimation Using Decision Tree Based Neural Nets Approach. / Yang, Hong-Tzer; Chang, Wen Yeau; Huang, Ching Lien.

In: IEEE Transactions on Power Delivery, Vol. 10, No. 1, 01.01.1995, p. 540-546.

Research output: Contribution to journalArticle

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