Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža

Delimar, Marko

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scientific master's theses

Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža

Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2001. urn:nbn:hr:168:558817

Delimar, Marko

University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Energy and Power Systems

Cite this document

APA 6th Edition

Delimar, M. (2001). Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:558817

MLA 8th Edition

Delimar, Marko. "Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2001. https://urn.nsk.hr/urn:nbn:hr:168:558817

Chicago 17th Edition

Harvard

Delimar, M. (2001). 'Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:558817

Vancouver

Delimar M. Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2001 [cited 2025 January 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:558817

IEEE

M. Delimar, "Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2001. Available at: https://urn.nsk.hr/urn:nbn:hr:168:558817

Cite this item: https://urn.nsk.hr/urn:nbn:hr:168:558817

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Metadata

Title	Određivanje topologije elektroenergetskog sustava primjenom neuronskih mreža
Title (english)	Power System Topology Identification Using Neural Networks
Author	Marko Delimar
Mentor	Zdravko Hebel (mentor)
Committee member	Ivica Pavić (predsjednik povjerenstva)
Committee member	Zdravko Hebel (član povjerenstva)
Committee member	Srete Nikolovski (član povjerenstva)
Granter	University of Zagreb Faculty of Electrical Engineering and Computing (Department of Energy and Power Systems) Zagreb
Defense date and country	2001-09-26, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Electrical Engineering Power Engineering
Universal decimal classification (UDC)	621.3 - Electrical engineering
Abstract	Procjena stanja elektroenergetskog sustava je osnovna funkcija za vođenje i analizu elektroenergetskog sustava. Kako se topološka struktura mreže tijekom pogona mijenja, prije procjene stanja potrebno je provjeriti ispravnost prijavljene topološke strukture sustava jer su u suprotnom moguće vrlo grube pogreške u procjeni stanja. U radu je prikazan model za provjeru topološke strukture elektroenergetskog sustava zasnovan za neuronskim mrežama. Postupak je podijeljen u dva dijela. Prvi dio predstavlja model za određivanje točnog broja mrežnih čvorišta, a drugi analizu njihove povezanosti. Uspoređeno je više arhitektura neuronskih mreža isprobanih na više elektroenergetskih mreža. Prikazani su i analizirani rezultati dobiveni primjenom višeslojnog perceptona učenog algoritmom povratnog prostiranja izlazne pogreške.
Abstract (english)	Power system state estimation is a basic function in power system control and analysis. The topological structure of the power system changes during power system operation and must be checked before state estimation to avoid gross error during state estimation. This paper present a model for identifying anomalies in power system topology based on neural networks. The procedure is divided into two parts: nodes and branch processing. Several types of neural networks are tried out on different power system network configurations. The results obtained using multilayer percepton with backpropagation learning algorithm are presented and analysed.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:168:558817
Study programme	Title: Postgraduate master programme in electrical engineering Study programme type: university Study level: postgraduate Academic / professional title: Magistar znanosti elektrotehnike (Magistar znanosti elektrotehnike)
Type of resource	Text
File origin	Born digital
Access conditions	Closed access
Terms of use
Repository	FER Repository
Created on	2019-04-19 08:47:40