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This study presents a comparative simulation of electrical steels with different grain orientations in three-phase dry-type power distribution transformers. Electrical steels modeled as three-phase transformer cores are analyzed and compared. In this context, time-dependent simulations of three-dimensional transformer models were performed using the coupling method based on finite element analysis to determine core losses and thermal behavior differences. This study reveals the effects of different grades of core materials on time-dependent core temperature depend on power losses and magnetic flux density. For this purpose, a 100 kVA three-strand three-phase dry-type transformer was used to simulate and prove the concept, and the simulation results were compared. As a result, according to mathematical calculations, core losses for M3, M4, and M5 were 298 W, 340 W, and 402 W, respectively, while the error rates between them were found to be 2.95%, 1.1%, and 5.5%, with the simulation results. The maximum temperature values obtained as a result of the time-dependent thermal analysis according to these loss values are 70.71°C, 70.724°C, and 80.619°C, respectively. These results show how important the material selection is in terms of design, efficiency, and transformer life. [ABSTRACT FROM AUTHOR]

Because natural and social resources are unevenly distributed over the earth's surface, socioeconomic developments differ in time and space. Although the most critical causes of inequality are natural or geographical reasons, the lack of energy supply-demand balance-specific to the region increases inequality. Undoubtedly, eliminating the supply-demand imbalance because of the increase in energy demand by costing energy cheaply will significantly reduce these differences. The existing electricity grid must be expanded or partially or completely replaced to meet the energy demand. This study aims to design a new electricity network or expand an existing network to meet consumers' needs by providing energy distribution with minimum cost and maximum quality. In this study, we analyzed the energy costs generated by re-planning a network that distributes electricity at different voltage levels to meet the increasing energy needs. We established a minimization function by determining the required transformer powers and their numbers considering the physical and electrical conditions to obtain the optimum network design. We analyzed the generated function by using a mixed-integer programming algorithm and a genetic algorithm in MATLAB. [ABSTRACT FROM AUTHOR]