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scientific master's theses
Pogonsko optimiranje razdjelnih mreža genetskim algoritmom
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2007. urn:nbn:hr:168:290511
Maras, Mladen
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Control and Computer Engineering

Cite this document

Maras, M. (2007). Pogonsko optimiranje razdjelnih mreža genetskim algoritmom (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:290511

Maras, Mladen. "Pogonsko optimiranje razdjelnih mreža genetskim algoritmom." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2007. https://urn.nsk.hr/urn:nbn:hr:168:290511

Maras, Mladen. "Pogonsko optimiranje razdjelnih mreža genetskim algoritmom." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 2007. https://urn.nsk.hr/urn:nbn:hr:168:290511

Maras, M. (2007). 'Pogonsko optimiranje razdjelnih mreža genetskim algoritmom', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 September 2024, https://urn.nsk.hr/urn:nbn:hr:168:290511

Maras M. Pogonsko optimiranje razdjelnih mreža genetskim algoritmom [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2007 [cited 2024 September 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:290511

M. Maras, "Pogonsko optimiranje razdjelnih mreža genetskim algoritmom", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2007. Available at: https://urn.nsk.hr/urn:nbn:hr:168:290511

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Metadata
TitlePogonsko optimiranje razdjelnih mreža genetskim algoritmom
Title (english)Distribution power network reconfiguration using genetic algorithm
AuthorMladen Maras
VIAF: 305685701
MentorNedjeljko Perić (mentor)
Committee memberIvica Pavić (član povjerenstva)
Committee memberNedjeljko Perić (član povjerenstva)
Committee memberMuharem Mehmedović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Control and Computer Engineering)
Zagreb
Defense date and country2007-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Process Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
621.3 - Electrical engineering
Abstract
U magistarskom radu pod nazivom "Pogonsko optimiranje razdjelnih mreža genetskim algoritmom" prikazuje se nova metoda za rekonfiguaciju razdjelnih mreža. Razvijena je i aplikacija u svrhu provjere razvijenog genetskog algoritma. Pogonsko optimiranje provodi se u svrhu smanjenja toplinskih gubitaka, povećanja raspoloživosti mreže i bolje raspodjele opterećenja uz poštivanje topoloških i pogonskih ograničenja. Kvaliteta nekog uklopnog stanja ocjenjuje se proračunom struja i padova napona, te proračunom raspoloživosti razdjelne mreže. Odabrana optimizacijska metoda je eliminacijski genetski algoritam s permutacijskim kodiranjem. Za stvaranje početnih rješenja razvijena su dva algoritma koja kreću od uklopnice "u dubinu" i "u širinu". Za operator križanja odabrano je ER križanje (eng. edge recombination). Razvijen je algoritam mutacije kojem se zadržava radijalna struktura mreže. Provjerom razvijenog genetskog algoritma na konkretnim razdjelnim mrežama potvrdila se njegova učinkovitost u smanjenju toplinskih gubitaka od 17% do 28%, povećanje raspoloživosti razdjelne mreže na četvrtoj decimali, te mogućnost rasterećenja preopterećenih dijelova mreže.
Abstract (english)
The master thesis “Distribution power network reconfiguration using genetic algorithm” proposes a new method for power network reconfiguration accounting constraints. An application for testing the proposed method is also developed. Reconfiguration of power distribution network is used to reduce Joule losses of power network, to enhance network reliability and to achieve better load balance of the system’s feeders while satisfying constraints. Load flow (calculation of currents and voltage drops) is used to evaluate quality of a particular network configuration. Proposed optimization method is an eliminating genetic algorithm with permutation coding. For evolving initial solutions (population) two algorithms are developed: "in depth" and "in breadth". Edge recombination operator constructs an offspring that inherits as much information as possible from the parent structures and is therefore chosen. Developed mutation algorithm does not violate the radial network. The proposed genetic algorithm has been tested on real distribution networks. Joule losses have been reduced from 17 % to 28 % and reliability has been enhanced at fourth decimal.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:290511
Study programmeTitle: Postgraduate master programe in computing
Study programme type: university
Study level: postgraduate
Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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RepositoryFER Repository
Created on2020-03-27 15:33:43

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