Design optimization of Earthing Transformers based on Differential Evolution Algorithms

Abstract

Differential Evolution (DE), a vector population based stochastic optimization method which is an improved version of Genetic Algorithm(GA) has been used for solving different problems with grounding of the isolated systems of distribution or interconnected networks. Earthing 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 the interconnected star earthing transformer. In this paper, an effective application of the combinatorial optimization algorithm based on Differential Evolution is proposed with the aim of minimizing the cost of the active part of wound core earthing 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. Our approach provides very good results, which are highly competitive with those generated by the compared EAs in constrained evolutionary optimization.