Optimal design of a furnace transformer by intelligent evolutionary methods
| Autor: | Mohd Noh Karsiti, K. S. Rama Rao |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Optimal design
Engineering Mathematical optimization business.industry Constrained optimization Energy Engineering and Power Technology Particle swarm optimization Control engineering Nonlinear programming law.invention Nonlinear system law Electrical and Electronic Engineering business Transformer Electric arc furnace |
| Zdroj: | International Journal of Electrical Power & Energy Systems. 43:1056-1062 |
| ISSN: | 0142-0615 |
| DOI: | 10.1016/j.ijepes.2012.06.019 |
| Popis: | This paper presents three intelligent evolutionary optimization techniques to investigate the optimal design parameters of a 3-phase furnace transformer. The transformer rating is derived from the operating conditions of a medium size direct arc furnace. Scatter Search (SS), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques are employed on the developed nonlinear mathematical model of the transformer for constrained optimization minimizing the cost. The design and analysis programs of the furnace transformer are developed using codes written in C++/C language. The optimal design data results validated by an example show the efficacy of the three intelligent techniques. Among the three methods, the optimal results obtained by GA and PSO techniques show the potential for implementing as efficient search techniques for design optimization of furnace transformers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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