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scientific master's theses
Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2000. urn:nbn:hr:168:937716
Kulenović, Džebel
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Kulenović, Dž. (2000). Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:937716

Kulenović, Džebel. "Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2000. https://urn.nsk.hr/urn:nbn:hr:168:937716

Kulenović, Džebel. "Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2000. https://urn.nsk.hr/urn:nbn:hr:168:937716

Kulenović, Dž. (2000). 'Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:937716

Kulenović Dž. Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2000 [cited 2024 December 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:937716

Dž. Kulenović, "Primjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2000. Available at: https://urn.nsk.hr/urn:nbn:hr:168:937716

Metadata
TitlePrimjena neuronskih mreža u distantnoj zaštiti visokonaponskih vodova
Title (english)Application of artificial neural networks to distance protection on HV lines
AuthorDžebel Kulenović
MentorAnte Marušić (mentor)
Committee memberAnte Marušić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2000, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Power Engineering
Universal decimal classification
(UDC)		621.3 - Electrical engineering
Abstract
Primjena neuronskih mreža u elektroenergetici, a jednako tako i u dostantnoj zaštiti, zadnjih je godina u stalnom porastu. Da bi se smanjio negativan utjecaj otpora na mjestu kvara u distantnoj zaštiti visokonaponskih vodova, u ovom je radu upotrebljen višeslojni perceptron, koji je učen Levenberg-Marquardt algoritmom. Poglavlja 2 i 3 obuhvaćaju poznata saznanja o razmatranoj problematici. U poglavlju 4 se opisuje razmatrana mreža i matematički model zasnovan na teoriji simetričnih komponenti. Poglavlje 5 objašnjava matematičke principe učenja pomoću algoritma sa povratnim rasprostiranjem pogreške i Levenberg-Marquardt algoritma. Poglavlja 6 do 8 prikazuju dobivene rezultate, analizu rezultata te zaključak. Višeslojni perceptron je ispitan simuliranjem pojave jednopolnog kratkog spoja uzduž dvostrano napajanog visokonaponskog dalekovoda, za različite iznose otpora na mjestu kvara te različite udaljenosti do mjesta kvara. Rezultati istraživanja su pokazali primjenjivost neuronskih mreža u distantnoj zaštiti i lokatoru kvara.
Abstract (english)
In the last few years use of artificial neural networks in power systems, and also in distance protection, is rapidly increasing. Multilayer perceptron with Levenberg-Marquardt algorithm are used to decrease negative influence of fault resistance in distance protection. Chapters 2 and 3 give the present knowledge concerning analysed topics. Chapter 4 explains the analysed network and the coresponding mathematical model based on symmetrical components. Chapter 5 explains mathematical background of multilayer perceptron. Basic and faster back-propagation lerning algorithm are also presented. Chapters 6 to 8 show the testing results, analisys of this results and conclusion. Multilayer perceptron with Levenberg-Marquardt algorithm are tested by simulating the occurrence of single phase-to-earth fault on different fault points along the HV line, varying the fault resistance. The testing results prove that the neural networks are useful to implement in distance protection and fault locator algorithm.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:937716
Study programmeTitle: Postgraduate master programme in electrical engineering
Study programme type: university
Study level: postgraduate
Academic / professional title: Magistar znanosti elektrotehnike (Magistar znanosti elektrotehnike)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2019-07-22 07:50:03