Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/8208
Title: | Design optimization of Rectifier Transformers | Authors: | Salkoski, Rasim Chorbev, Ivan |
Keywords: | Optimization, Rectifier transformer, Design optimization methodology, Differential Evolution algorithm, Optimization methods, Wound core type rectifier transformer | Issue Date: | 8-May-2020 | Publisher: | Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia | Series/Report no.: | CIIT 2020 full papers;2 | Conference: | 17th International Conference on Informatics and Information Technologies - CIIT 2020 | Abstract: | Optimization refers to finding one or more feasible solutions, which correspond to extreme values of one or more objectives. The need for finding such optimal solutions in a problem comes mostly from the extreme purpose of either designing a solution for minimum possible cost of fabrication, or for maximum possible reliability, or others. Because of such extreme properties of optimal solutions, optimization methods are of great importance in practice, particularly in engineering design, scientific experiments and business decision-making. Rectifier transformers deserve extensive treatment in the field of research and production, due to the fact that the electric energy undergoes several transformations on its way from generators to the consumers i.e. rectifiers. In this paper, an effective application of the population based search Differential Evolution algorithm is proposed with the aim of minimizing the cost of the active part of wound core rectifier transformers. The constraints resulting from international specifications and customer needs are taken into account. The Objective Function that is optimized is a minimization dependent on multiple input variables. All constraints are normalized and modeled as inequalities. | URI: | http://hdl.handle.net/20.500.12188/8208 |
Appears in Collections: | International Conference on Informatics and Information Technologies |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
CIIT2020_paper_2.pdf | 466.94 kB | Adobe PDF | View/Open |
Page view(s)
125
checked on Jul 24, 2024
Download(s)
105
checked on Jul 24, 2024
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.