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