Artificial Neural Network Approach for Locating Faults in Power Transmission System (CROSBI ID 598386)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
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