A comparative analysis of multi-objective and multialgorithm approaches for the optimal design of distribution transformers

Abstract

A comparative analysis of multi-objective and multi-algorithm approaches for the optimal design of distribution transformers 34A comparative analysis of multi-objective and multialgorithm approaches for the optimal design of distribution transformers ABSTRACTThis paper presents the sizing of three phase transformer using four intelligent algorithms namely geometric programming, genetic algorithm, simulated annealing, and particle swam optimization. Four independent objective functions and eight constraints were used. The comparative analysis carried out on the results obtained from these intelligent algorithms shows that all the outputs from the intelligent algorithms are the same. The fastness of results shows that geometric programming is the fastest, while genetic algorithm, simulated annealing, and particle swam optimization followed in that order. The output results from the cost objective function were compared with the results obtained by Masood (2012) and it showed that money was saved in the following order, 6.4%, 16.32%, 10.63% and 16.79% respectively for geometric programming, genetic algorithm, simulated annealing, and particle swam optimization.