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Optimization of Transformer Design using Bacterial Foraging Algorithm

by S. Subramanian, S. Padma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 19 - Number 3
Year of Publication: 2011
Authors: S. Subramanian, S. Padma
10.5120/2338-3049

S. Subramanian, S. Padma . Optimization of Transformer Design using Bacterial Foraging Algorithm. International Journal of Computer Applications. 19, 3 ( April 2011), 52-57. DOI=10.5120/2338-3049

@article{ 10.5120/2338-3049,
author = { S. Subramanian, S. Padma },
title = { Optimization of Transformer Design using Bacterial Foraging Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 19 },
number = { 3 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 52-57 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume19/number3/2338-3049/ },
doi = { 10.5120/2338-3049 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:04.336318+05:30
%A S. Subramanian
%A S. Padma
%T Optimization of Transformer Design using Bacterial Foraging Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 19
%N 3
%P 52-57
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Transformers are widely used in electric power system to perform the primary functions, such as voltage transformation and isolation. So the transformer design is emphasize. In this paper, a transformer design optimization method is proposed aiming at designing the transformer to optimize the efficiency and cost. The design optimization of transformer is formulated as unconstrained non linear multivariable programming technique. Five independent variables and three constraints are taken to meet the requirement of the design. A heuristic search technique Bacterial Foraging Algorithm (BFA) is used to solve the optimization problem. The effectiveness of the proposed approach has been tested with two sample transformers and the simulation results are compared against with the conventional method, Simulated Annealing (SA) technique and Particle Swarm Optimization (PSO) method. The simulation results reveal that the proposed method determines the optimal variables of transformer long with the performance parameters efficiently and accurately.

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Index Terms

Computer Science
Information Sciences

Keywords

Transformer design optimization cost efficiency bacterial foraging algorithm

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