DocumentCode :
3192385
Title :
A New Protection Detection Technique for High Impedance Fault Using Neural Network
Author :
Eissa, M.M. ; Sowilam, G.M.A. ; Sharaf, A.M.
Author_Institution :
SMIEEE, Department of Electrical Engineering, Faculty of Engineering, Helwan University, EGYPT. mmmeissa@yahoo.com
fYear :
2006
fDate :
38899
Firstpage :
146
Lastpage :
151
Abstract :
The paper presents the application of Neural Network technique as a pattern recognition to high impedance faults (HIFs). The relay is based on a novel low-frequency (3rd and 5th harmonic feature diagnostic vector). The currents and voltages are used as a featured extracted signals for fault discrimination. The focus of this paper is to design a robust ANN-based relay, which can determine the high impedance low current faults on distribution radial electrical systems. A variety of faults and system conditions have been simulated to evaluate the reliability and sensitivity of the proposed technique.
Keywords :
Fault detection; Feature extraction; Impedance; Neural networks; Pattern recognition; Protection; Protective relaying; Relays; Robustness; Voltage; ANN based relaying; EHV Transmission line; Matlab/Simulink; Non linear ARC model; Pattern recognition; Protective Relaying;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering, 2006 Large Engineering Systems Conference on
Conference_Location :
Halifax, NS, Canada
Print_ISBN :
1-4244-0556-4
Electronic_ISBN :
1-4244-0557-2
Type :
conf
DOI :
10.1109/LESCPE.2006.280378
Filename :
4059384
Link To Document :
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