DocumentCode :
2572882
Title :
Artificial neural network based fault locator for EHV transmission system
Author :
Joorabian, M.
Author_Institution :
Dept. of Electr. Eng., Shahid Chamran Univ., Ahwaz, Iran
Volume :
3
fYear :
2000
fDate :
29-31 May 2000
Firstpage :
1003
Abstract :
This paper describes the design and implementation of an accurate fault location technique using artificial neural networks (ANN) for the 400 kV Iranian transmission systems. The technique utilises voltage and current fault data at one line end only. These values are stored as waveform samples by a digital fault recorder (DFR) in the substations. The instantaneous three phase voltages and currents derived at the fault locator point on the line which contain fault information at different frequencies are used to train and test the artificial neural network (ANN). The paper presents the result of simulation studies to determine the performance and practical implementation of the technique.
Keywords :
digital instrumentation; fault location; neural nets; power system analysis computing; power transmission faults; substations; 400 kV; ANN; EHV transmission system; Iranian transmission systems; artificial neural network; current fault data; digital fault recorder; fault information; fault location technique; fault locator; fault locator point; instantaneous three phase currents; instantaneous three phase voltages; substations; voltage fault data; waveform samples; Artificial neural networks; Circuit faults; Fault location; Power system faults; Power system modeling; Power system simulation; Power system transients; Power transmission lines; Substations; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean
Print_ISBN :
0-7803-6290-X
Type :
conf
DOI :
10.1109/MELCON.2000.879703
Filename :
879703
Link To Document :
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