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Artificial Neural Network Approach for Locating Faults in Power Transmission System (CROSBI ID 598386)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Teklić, Ljupko ; Filipović-Grčić, Božidar ; Pavičić, Ivan Artificial Neural Network Approach for Locating Faults in Power Transmission System // IEEE Eurocon 2013 Conference : proceedings / Kuzle, Igor ; Capuder, Tomislav ; Pandžić, Hrvoje (ur.). Zagreb: Institute of Electrical and Electronics Engineers (IEEE), 2013. str. 1425-1430

Podaci o odgovornosti

Teklić, Ljupko ; Filipović-Grčić, Božidar ; Pavičić, Ivan

engleski

Artificial Neural Network Approach for Locating Faults in Power Transmission System

This paper presents fault location recognition in transmission power system using artificial neural network (ANN). Single phase short circuit on 110 kV transmission line fed from both ends was analyzed with various fault impedances, since it is the most common fault in power system. Load flow and short circuit calculations were performed with EMTP-RV software. Calculation results including currents and voltages at both line ends were used for training ANN in Matlab in order to obtain correct fault location and fault impedance, even for those cases that ANN has never encountered before. The network was trained with back propagation algorithm. Test results show that this approach provides robust and accurate location of faults for a variety of power system operating conditions and gives an accurate fault impedance assessment.

fault location; transmission lines; feed forward neural network; artificial neural network

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Podaci o prilogu

1425-1430.

2013.

objavljeno

Podaci o matičnoj publikaciji

IEEE Eurocon 2013 Conference : proceedings

Kuzle, Igor ; Capuder, Tomislav ; Pandžić, Hrvoje

Zagreb: Institute of Electrical and Electronics Engineers (IEEE)

978-1-4673-2231-7

Podaci o skupu

IEEE Eurocon 2013 Conference

predavanje

01.07.2013-04.07.2013

Zagreb, Hrvatska

Povezanost rada

Elektrotehnika