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doctoral thesis
Procjena statičke sigurnosti elektroenergetskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2005. urn:nbn:hr:168:083611
Delimar, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Energy and Power Systems

Cite this document

Delimar, M. (2005). Procjena statičke sigurnosti elektroenergetskih mreža (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:083611

Delimar, Marko. "Procjena statičke sigurnosti elektroenergetskih mreža." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2005. https://urn.nsk.hr/urn:nbn:hr:168:083611

Delimar, Marko. "Procjena statičke sigurnosti elektroenergetskih mreža." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2005. https://urn.nsk.hr/urn:nbn:hr:168:083611

Delimar, M. (2005). 'Procjena statičke sigurnosti elektroenergetskih mreža', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:083611

Delimar M. Procjena statičke sigurnosti elektroenergetskih mreža [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2005 [cited 2024 April 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:083611

M. Delimar, "Procjena statičke sigurnosti elektroenergetskih mreža", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2005. Available at: https://urn.nsk.hr/urn:nbn:hr:168:083611

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Metadata
TitleProcjena statičke sigurnosti elektroenergetskih mreža
Title (english)Static Security Assessment of Power Networks
AuthorMarko Delimar
MentorZdravko Hebel (mentor)
Committee memberIvica Pavić (član povjerenstva)
Committee memberZdravko Hebel (član povjerenstva)
Committee memberSrete Nikolovski (član povjerenstva)
Committee memberSven Lončarić (član povjerenstva)
Committee memberVladimir Mikuličić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Energy and Power Systems)
Zagreb
Defense date and country2005-10-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Power Engineering
Universal decimal classification
(UDC)		621.3 - Electrical engineering
Abstract
Vođenje modernog elektroenergetskog sustava je balans između ekonomskih i sigurnosnih zahtjeva. Zadatak ovog rada bio je ispitati mogućnosti primjene neuronskih mreža pri procjeni statičke sigurnosti mreže elektroenergetskog sustava. U radu su prikazani osnovni modeli za procjenu stanja i statičku procjenu sigurnosti elektroenergetskih mreža, kao i pregled primjena neuronskih mreža u elektroenergetici. U radu je predložena metoda za procjenu statičke sigurnosti elektroenergetskih mreža temeljena na višeslojnom perceptronu, čiji su ulazni podaci tokovi snaga u stacionarnom stanju elektroenergetske mreže, a izlazni podaci indeksi djelovanja povezani s pogonskim prekoračenjima nakon ispada elemenata mreže. Neuronska mreža učena je povratnim prostiranjem izlazne pogreške. U radu je prikazana i metoda za procjenu topološke strukture elektroenergetske mreže temeljena na neuronskim mrežama koja je poslužila kao temelj za analizu ispada. Predložene metode testirane su na IEEE test mreži od 24 čvorišta pri čemu su simulirana različita pogonska stanja.
Abstract (english)
The modern operation of an electric power system is often a balance between economic and security issues. The main goal of this research was to determine the possibilities of applying an artificial neural network to the power system static security assessment. In this thesis, basic state estimation and security assessment models were presented, as well as a short overview of neural networks applications to electric power engineering. This thesis has explored a multilayer perceptron neural network for static security assessment with power flows as inputs and post contingency performance indices as outputs. A backpropagation learning algorithm was used. As a basis for outage analysis, a neural network for topology identification was also discussed. The performance of the proposed methods was evaluated for different operating conditions using the IEEE 24bus test system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:083611
Study programmeTitle: Doctoral study programme "Electrical Engineering and Computing"
Study programme type: university
Study level: postgraduate
Academic / professional title: doktor/doktorica znanosti, po-dručje tehničkih znanosti (doktor/doktorica znanosti, po-dručje tehničkih znanosti)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
RepositoryFER Repository
Created on2019-07-10 09:13:38

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