This paper highlights the transformer design optimi zation using genetic algorithm (GA) and simulated a(SA). Any optimization problem, a given objective functio n is to be minimized keeping in view the constraints . Similarly, transformer design optimization problem involves minimizing the total mass (or cost) of the core and wire material by satisfying constraints imposed by international standards and transformer user specification. The constraints include appropr iate limits on efficiency, voltage regulation, temperature rise, no-load curre nt and winding fill factor. The design optimizations seek a constrained minimum mass (or cost) solution by optimally settin g the transformer geometry parameters and require m agnetic properties. This paper solves the said design problem by using genet ic algorithm (GA) and simulated annealing (SA) tech niques. The results of geometric programming (GP) technique have been comp ared with the results obtained by applying GA and SA techniques. It is quite evident from the results that the dimensions as well as mass of copper and core have been reduced in comparison to GP using same set of constraints. Therefore, the paper presents improved design of power transformer by th ese two techniques. The results of GA and SA have been obtained using optim ization tool box MATLAB Release 9.1 which have not bapplied for power transformer design so far. First it provides efficient and reliable solution for the design optimization problem with several variables. Second, it guaranteed that the o btained solution is global optimum. Hence paper dem onstrates a better and efficient solution to high frequency power transfo rmer design.
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