magistrsko delo
Jan Šubelj (Author), Jurij Mihelič (Mentor)

Abstract

Načrtovanje močnostnih transformatorjev je zahteven proces, ki potrebuje obsežno znanje in izkušnje. Namen magistrskega dela je razvoj genetskega algoritma, ki olajša delo projektantom pri načrtovanju močnostnih transformatorjev. Magistrska naloga prikaže izdelavo in optimizacijo elitističnega genetskega algoritma večciljne optimizacije z omejitvami za načrtovanje transformatorjev. Predstavljene so osnove projektiranja in izračuna karakteristik transformatorja. Genetski algoritmi so opisani, predstavljene so implementirane razširitve in izboljšave. Prikazano je nastavljanje metaparametrov na optimalno vrednost. Predstavljene so odvisnosti rezultatov od metaparametrov. Rezultati so primerjani z že izdelanimi transformatorji podjetja Kolektor Etra in z rezultati prilagojenega algoritma vzpenjanja. Implementirani algoritem vrača dobre rešitve, na podlagi katerih si projektant lahko pomaga pri načrtovanju transformatorja. V določenih primerih so rešitve algoritma boljše od že izdelanih transformatorjev. Rešitve genetskega algoritma so veliko boljše od rešitev prilagojenega algoritma vzpenjanja.

Keywords

večciljna optimizacija;genetski algoritem;močnostni transformator;računalništvo;računalništvo in informatika;magisteriji;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [J. Šubelj]
UDC: 004.89(043.2)
COBISS: 32478723 Link will open in a new window
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Downloads: 123
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Other data

Secondary language: English
Secondary title: Development of a multi-objective genetic algorithm for power transformer design
Secondary abstract: The design of power transformers is a demanding process that requires extensive knowledge and experience. The purpose of the master's thesis is the development of a genetic algorithm that facilitates the work of designers in the design of power transformers. This master's thesis presents the fabrication and optimisation of an elitist multi-objective genetic algorithm with constraints for transformer design. The basics of transformer design and calculation are presented. Genetic algorithms are described, implemented extensions and improvements are presented. The setting of metaparameters to the optimal value is shown. The dependencies of the results on metaparameters are presented. The results are compared with transformers that are already manufactured by the company Kolektor Etra and with the results of the adapted hill-climbing algorithm. The implemented algorithm returns reasonable solutions which can help the designer in the process of the design of the transformer. In some instances, the algorithm solutions are better than already manufactured transformers. The solutions of the genetic algorithm are much better than the solutions of the customised hill-climbing algorithm.
Secondary keywords: multiobjective optimization;genetic algorithm;power transformer;computer science;computer and information science;master's degree;
Type (COBISS): Master's thesis/paper
Study programme: 1000471
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 84 str.
ID: 12044773