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Title:SELEKTIVNO DOLOČANJE OKVARJENEGA IZVODA OB ZEMELJSKEM STIKU V DISTRIBUCIJSKEM OMREŽJU
Authors:ID Jelenc, Bogomil (Author)
ID Pihler, Jože (Mentor) More about this mentor... New window
Files:.pdf MAG_Jelenc_Bogomil_2016.pdf (4,53 MB)
MD5: B8A01DD2372585A8BACDF29B157744AE
 
Language:Slovenian
Work type:Master's thesis
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Umetne nevronske mreže postajajo zelo uporabne za podporo dispečerjem pri vodenju obratovanja distribucijskih elektroenergetskih sistemov. Odlično se izkažejo predvsem pri prepoznavanju vzorcev različnih signalov, kar je v bistvu osnova delovanja zaščitnih naprav v elektroenergetskem sistemu. Magistrsko delo podaja način določanja okvarjenega izvoda v razdelilni transformatorski postaji pri zemeljskem stiku, tudi visokoohmskem, z uporabo nevronske mreže s povezavami naprej (feed forward artificial neuron network). Nevronska mreža je naučena z nadzorovano metodo z uporabo algoritma povratnega napredovanja (angl. backpropagation). Za učenje so bili uporabljeni posnetki realne okvare. Validacija nevronske mreže je prav tako narejena na posnetkih realne okvare vendar ne istih kot so bili uporabljeni za učenje. Rezultati so pokazali izjemno zanesljivost določanja prisotnosti okvare v sistemu in določanja okvarjenega izvoda.
Keywords:nevronska mreža, umetni nevron, umetna inteligenca, distribucijsko omrežje, zemeljski stik
Place of publishing:Maribor
Publisher:[B. Jelenc]
Year of publishing:2016
PID:20.500.12556/DKUM-61934 New window
UDC:004.383.8:004.896(043)
COBISS.SI-ID:19781398 New window
NUK URN:URN:SI:UM:DK:5DLFTFSG
Publication date in DKUM:13.09.2016
Views:2086
Downloads:174
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
JELENC, Bogomil, 2016, SELEKTIVNO DOLOČANJE OKVARJENEGA IZVODA OB ZEMELJSKEM STIKU V DISTRIBUCIJSKEM OMREŽJU [online]. Master’s thesis. Maribor : B. Jelenc. [Accessed 8 January 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=61934
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Secondary language

Language:English
Title:DETECTING A FAULTY FEEDER BY USING AN ARTIFICIAL NEURAL NETWORK
Abstract:Recent developments indicate that the Artificial Neural Networks (ANNs) may be useful assisting the power system dispatchers at their work. The study presents an approach to detection a faulty feeder during a phase to earth fault ( also a high impedance fault) in a power distribution system using a feed-forward ANN. In the proposed ANN algorithm, the standard back-propagation technique with a sigmoid activation function is used. ANN is trained with real data obtained with a disturbance recorder during an actual fault. The study results show that the proposed algorithm performs excellently in detecting the phase to earth faults and locating the faulty feeder.
Keywords:Artificial Neural Network, Neuron, Earth fault, power distributing system


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