Multiobjective Optimization Techniques Applied to Three-Phase Transformers Designs

The aim of this research is to present the studies carried out to design three-phase core type distribution transformers, with the aid of optimization techniques. The minimization of losses is presented in two steps, first through the use of a mono-objective function, and second with the use of multi-objective function to minimize losses and the total mass of the active part of the transformer. The algorithms used are: Differential Evolution and Particle Swarm Optimization, their performances are compared through the results obtained. The main project parameters, such as core dimensions, total losses, no load current and the energizing current are estimated analytically through OCTAVE software. The analysis of magnetic flux density in the core is simulated using the Finite Element Method. Multiobjective optimization allows working with two or more conflicting objectives, and at each iteration, it stores the various non-dominant Pareto Front solutions, helping designers to choose the solution that best meets their needs. The results obtained with the mono-objective and multiobjective optimization techniques were interesting to minimize the losses and/or cost of the project