On-line power system fault estimation using connectionist models

Hong Tzer Yang, Wen Yeau Chang, Chi Fung Chen, Ching Lien Huang

Research output: Contribution to journalConference articlepeer-review


This paper proposes a new connectionist (or neural network) expert diagnostic system for on-line fault diagnosis of a power substation. The connectionist expert diagnostic system has similar profile of an expert system, but can be constructed much more easily from elemental samples. These sample indicate the association of fault with their protective relays and breakers, as well as the bus voltage and feeder currents. Through an elaborately designed structure, these two types of alarm signals are processed by different connectionist models. The outputs of the connectionist models are then integrated to provide the final conclusion with confidence level. The proposed approach has been practically verified testing on a typical Taiwan Power (Taipower) secondary substation. The test results suggest our system can be implemented by various electric utilities with relatively low customization effort.

Original languageEnglish
Pages (from-to)871-877
Number of pages7
JournalIEE Conference Publication
Issue number388
Publication statusPublished - 1994 Jan 1
EventProceedings of the 2nd International Conference on Advances in Power System Control, Operation & Management - Hong Kong, Hong Kong
Duration: 1993 Dec 71993 Dec 10

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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