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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]

The electron drift velocity, mean energy, ionization, attachment, effective ionization coefficient, limit electrical field, and synergism of pure CHF3 (fluoroform), pure CF4 (tetrafluoromethane), and CHF3+CF4 gas mixtures are calculated by Boltzmann equation analysis in a wide range of density normalized electrical fields (E/N). The finite difference method is used to solve the two-term approximation of the Boltzmann equation under steady-state Townsend conditions. To our knowledge, no previous electron swarm parameters of these mixtures have been published. At constant E/N values, the electron mean energies and drift velocities increase with decreasing CHF3 content. The addition of CF4 into the mixture increases the attachment coefficient but reduces the ionization coefficient since CF4 is more electronegative than CHF3. Furthermore, the limit electrical fields increase with increasing CF4 concentration. [ABSTRACT FROM AUTHOR]

This paper presents a filled function method to solve economic load dispatch (ELD) of the thermal unit. The proposed method can take care of ELD considering nonlinearity such as valve point loading. The effectiveness of the proposed algorithm has been verified on three different test systems with equality and inequality constraint. Simulation results show that the filled function method is less sensitive to initial values of parameters and is more effective than other previously developed algorithms. In addition, the proposed algorithm is highly promising for the large-scale system. [ABSTRACT FROM AUTHOR]

In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well. [ABSTRACT FROM AUTHOR]