Genetic algorithms and their variants have been extensively used for solving combinatorial optimization problems. One area of great importance that can benefit from the effectiveness of such algorithms is electric energy distribution. 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. In that regard, special interest is dedicated to the minimization of production and exploitation costs of a transformer. In the paper the combinatorial optimization algorithm based on Differential Evolution is described and applied to the problem of minimizing the cost of the active part of wound core distribution transformers. Constraints imposed both by international specifications and customer needs are taken into account. The Objective Function that is optimized is a minimization dependent on multiple input variables. Constraints are normalized and modeled as inequalities.
Combinatorial optimization, Transformer design optimization methodology, Differential Evolution algorithm, Optimization methods, distribution transformer, Wound core type transformer
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