Skip to the main content

Technical gazette, Vol. 29 No. 5, 2022.

Original scientific paper

https://doi.org/10.17559/TV-20220114203522

FEM-based Modeling and Optimization of Dry-Type Transformers with Metaheuristic Algorithms

Seda Kul orcid id orcid.org/0000-0001-8278-4723 ; Karamanoglu Mehmetbey University, Engineering Faculty, Department of Electrical and Electronics Engineering, 70200 Karaman, Turkey
Suleyman Sungur Tezcan orcid id orcid.org/0000-0001-6846-8222 ; Gazi University, Engineering Faculty, Department of Electrical and Electronics Engineering, 06500 Ankara, Turkey
Huseyin Duysak orcid id orcid.org/0000-0002-2748-0660 ; Karamanoglu Mehmetbey University, Engineering Faculty, Department of Electrical and Electronics Engineering, 70200 Karaman, Turkey
Seyit Alperen Celtek orcid id orcid.org/0000-0002-7097-2521 ; Karamanoglu Mehmetbey University, Engineering Faculty, Department of Energy Systems Engineering, 70200 Karaman, Turkey

Full text: english pdf 1.863 Kb

page 1678-1685

downloads: 362

cite

Abstract

Transformer optimization is a programming problem with an objective function for calculating the characteristics of a transformer in detail according to user requirements. Especially in recent years, efficient and optimum design of the transformer has become increasingly important. This study presents a comparative analysis of the application of metaheuristic optimization algorithms in transformer design for maximum efficiency of a three-phase dry-type transformer. In addition, transformer modeling was done using FEM analysis, and its magnetic characteristics were shown. The main contribution of this paper is to optimize the determined basic design parameters with optimization methods that have not been used in transformer optimization before and to maximize efficiency by reducing losses. During this process, using the loss constants of the materials in the basic loss equation for core loss, this process was tried to be carried out without any change in the method in applications to be made with different materials. This situation also strengthens the accuracy of the applied method. Crow Search (CSA), Moth-Flame Optimization (MFO), Vortex Optimization (VOA), Particle Swarm Optimization (PSO), and Social Learning-Particle Swarm Optimization (SL-PSO) algorithms were used in the study. The loss values were obtained by performing loaded and unloaded FEM analysis with the ANSYS/Maxwell program. As a result, the best result was obtained with SL-PSO as max 99,05%.

Keywords

dry-type transformer; energy efficiency; metaheuristic optimizations; optimization, SL-PSO

Hrčak ID:

281684

URI

https://hrcak.srce.hr/281684

Publication date:

15.10.2022.

Visits: 726 *