DocumentCode :
3245081
Title :
Three-phase fault location based on Multiple Classifier Systemin double-circuit transmission lines
Author :
Chan, Patrick P K ; Zhu, Jing ; Qiu, Zid-Wei
Author_Institution :
Machine Learning & Cybern. Res. Center, South China Univ. of Technol., Guangzhou, China
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
250
Lastpage :
254
Abstract :
Fault location estimation, which can actually be addressed as a classification or categorization problem, is a vital feature in protective relaying scheme for power transmission lines. In this paper, a novel three-phase fault location approach based on a Multiple Classifier System (MCS) not only using the information of the faulty lines but also considering others lines adjacent with the faulty line. Meanwhile, the number of samples used as an input also can have considerable effects on accuracy. In our proposed method, each base classifier predicts the fault location according to the information of different transmission line based on different number of samples as an input. Experimental results show that the better performance is achieved by the proposed method than the MLPs only using the information of the faulty line.
Keywords :
fault diagnosis; pattern classification; power engineering computing; power transmission faults; power transmission lines; relay protection; MCS; MLP; base classifier; categorization problem; classification problem; fault location estimation; faulty lines information; multiple classifier system double-circuit transmission; power transmission lines; protective relaying scheme; three-phase fault location approach; Artificial neural networks; Circuit faults; Fault location; Power system dynamics; Power transmission lines; Transmission line measurements; Classifier; Double circuit transmission line; Fault location; MCS; Three-Phase;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2158-5695
Print_ISBN :
978-1-4673-1534-0
Type :
conf
DOI :
10.1109/ICWAPR.2012.6294787
Filename :
6294787
Link To Document :
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