On-line fault diagnosis of power substation using connectionist expert system

Hong Tzer Yang, Wen Yeau Chang, Ching Lien Huang

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

This paper proposes a new connectionist (or neural network) expert system for on-line fault diagnosis of a power substation. The Connectionist Expert Diagnosis System has similar profile of an expert system, but can be constructed much more easily from elemental samples. These samples associate the faults with their protective relays and breakers as well as the bus voltages and feeder currents. Through an elaborately designed structure, alarm signals are processed by different connectionist models. The output of the connectionist models is then integrated to provide the final conclusion with a confidence level. The proposed approach has been practically verified by testing on a typical Taiwan Power (Taipower) secondary substation. The test results show that rapid and exactly correct diagnosis is obtained even for the fault conditions involving multiple faults or failure operation of protective relay and circuit breaker. Moreover, the system can be transplanted into various substations with little additional implementation effort.

Original languageEnglish
Pages (from-to)323-331
Number of pages9
JournalIEEE Transactions on Power Systems
Volume10
Issue number1
DOIs
Publication statusPublished - 1995 Feb

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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