Abstract
The first step in the transformer design process is to find the active part’s key design parameters. This is a non-linear mathematical optimisation task, which becomes more complex if the economic conditions are considered by the capitalisation of the losses. Geometric programming combined with the method of branch and bound can be an effective and accurate tool for this task even in the case of core-form power transformers, when formulating the short-circuit impedance in the required form is problematic. Most of the preliminary design methods consider only the active part of the transformer and the capitalised costs in order to determine the optimal key design parameters. In this paper, an extension of this meta-heuristic transformer optimisation model, which takes the cost of the insulating oil and the cooling equipment into consideration, is presented. Moreover, the impact of the new variables on the optimal key design parameters of a transformer design is examined and compared with the previous algorithm in two different economic scenarios. Significant difference can be found between the optimal set of key-design parameters if these new factors are considered.