Abstract:
Transformer design optimization methods presented in the literature rarely yield solutions directly applicable in production; the design engineer usually needs to convert the theoretical solution to a practical one. This problem is addressed in this paper, and a discrete transformer design optimization method is proposed that yields solutions with commercially available or productionally feasible dimensions, thus eliminating the need for further efforts of the design engineer to make the theoretical solution a feasible one. The cuckoo search, a nature-inspired metaheuristic algorithm, is used as the optimization algorithm in this study, and it is shown that the guaranteed global optimum solution is attained in a single run. Furthermore, a simple method is proposed to reduce the number of objective function and constraint calculations. The method is based on skipping calculations for design vectors recurring during the search process by use a caching technique. It is envisaged that the use of the proposed method will make a significant contribution to the streamlining of the quotation and design processes in the transformer industry as well as standardization of production materials.
