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Three-phase fault location based on Multiple Classifier Systemin double-circuit transmission lines

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3 Author(s)
Chan, P.P.K. ; Machine Learning & Cybern. Res. Center, South China Univ. of Technol., Guangzhou, China ; Jing Zhu ; Zhi-Wei Qiu

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.

Published in:

Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on

Date of Conference:

15-17 July 2012

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