NDLI: Study on Fault Line Detection Based on Genetic Artificial Neural Network in Compensated Distribution System

Content Provider	IEEE Xplore Digital Library
Author	Tao Ji Qingle Pang Xinyun Liu
Copyright Year	2006
Description	Author affiliation: Sch. of Inf. & Control Eng., Weifang Univ. (Tao Ji)
Abstract	The faulty line detection of single phase to earth fault in power system with neutral grounding via arc suppression coil has not been well solved. The commonly used single faulty line detection methods, such as wavelet transform method, the fifth harmonic current method and zero sequence current active components method, etc., can only process partial fault information, so their reliability of faulty line detection is not satisfied. By means of constructing both relative fault measurement function and confirmable fault measurement function the fault measurement function of each faulty line detection method is determined, then using genetic neural network the intelligent fusion of practical fault measurements of those faulty line detection methods is conducted, thereby the faulty line detection result with higher reliability can be obtained. Simulation results by EMTP show that the faulty line detection result by the proposed method is more precise and possesses stronger robustness
Starting Page	1427
Ending Page	1431
File Size	1316534
Page Count	5
File Format	PDF
ISBN	1424405289
DOI	10.1109/ICIA.2006.305965
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Coils Grounding Artificial neural networks Power system harmonics Electrical fault detection compensated distributon network Power system faults fault line detection Phase detection Fault detection Genetics Genetic neural network Power system reliability
Content Type	Text
Resource Type	Article

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