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