Comparison of Heuristic Approaches in Weight Optimization of Different Power Levels Transformers

Abstract

ABSTRACT In this study, the weight of distribution type transformers and power transformers, which are used extensively in the industry, is optimized. A heuristic approach that uses the Firefly algorithm, Ant Colony algorithm, and the Bee algorithm to determine the weight of transformers is described. Optimization of the iron weight components effective in the weight of a transformer to be produced in multi-type is provided. It is aimed to reduce the transformer cost, increase the life cycle of the transformer, and increase the efficiency by obtaining the optimum current density (s) and iron section (C) values which are the variable parameters used in the iron weight calculation of the transformer. In the study, it is determined that heuristic optimization algorithms, which provide more effective and efficient values than traditional approaches, give better results. These popular algorithms, in the weight parameters of 50 and 1000 kVA transformer powers, can obtain a lower weight value of 9.6% with the weight obtained by the Bee algorithm, 7.4% by the Ant Colony algorithm and 11% by the firefly algorithm than the weight obtained through the classical method. According to the heuristic optimization results, it shown that optimum 50 and 1000 kVA transformer weights can be determined and less costly transformer designs can be made.