DocumentCode :
1361288
Title :
On-line fault diagnosis of distribution substations using hybrid cause-effect network and fuzzy rule-based method
Author :
Chen, Wen-Hui ; Liu, Chih-Wen ; Tsai, Men-Shen
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Volume :
15
Issue :
2
fYear :
2000
fDate :
4/1/2000 12:00:00 AM
Firstpage :
710
Lastpage :
717
Abstract :
A correct and rapid inference is required for practical use of an online fault diagnosis in power substations. This paper proposes a novel approach for on-line fault section estimations and fault types identification using the hybrid cause-effect network/fuzzy rule-based method in distribution substations. A cause-effect network, which is well suited to parallel processing, represents the functions of protective relays and circuit breakers for selection of faulted sections. Therefore the inference speed can be improved significantly. In order to deal with the uncertainties involved in the process of clarifying faults, a fuzzy rule-based method is derived. The proposed approach has been practically verified by testing on a typical Taiwan Power Company´s (Taipower) secondary substation. The experimental results reveal that the correct and rapid diagnosis is obtained even for the fault domains involving multiple faults and failure operations of protective devices. Moreover, it is easy to implement and transplant into different substations
Keywords :
EMTP; fault diagnosis; parallel processing; power distribution faults; power system analysis computing; power system identification; substations; Taiwan; circuit breakers; computer simulation; distribution substations; fuzzy rule-based method; hybrid cause-effect network; online fault diagnosis; parallel processing; protective relays; Artificial neural networks; Automatic control; Circuit breakers; Circuit faults; Fault diagnosis; Power system protection; Power system relaying; Protective relaying; SCADA systems; Substation protection;
fLanguage :
English
Journal_Title :
Power Delivery, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8977
Type :
jour
DOI :
10.1109/61.853009
Filename :
853009
Link To Document :
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