Optimal Design of Flux Diverter Using Genetic Algorithm for Axial Short Circuit Force Reduction in HTS Transformers

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In: IEEE Transactions on Applied Superconductivity, 30(2020), 1, S. 1 - 8
Format: E-Article
Sprache: Englisch
veröffentlicht: IEEE
ISSN: 1051-8223
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Details: The appealing advantages of high-temperature superconducting (HTS) power transformers over conventional ones have attracted transformer manufacturing companies, power companies, research institutes, and universities worldwide to conduct research and development in this field. Unfortunately, HTS transformers are more vulnerable to mechanical stresses than conventional transformers. The results of the interaction between current carrying windings and leakage magnetic fluxes are the electromagnetic forces, which act on transformer windings. Under short circuit events, these forces are remarkable, and, therefore, catastrophic failure of transformer may arise. Flux-diverter applications have been reported in earlier literatures for increasing critical current or decreasing ac losses in HTS transformers. In this paper, a genetic algorithm based method is employed for the optimal design of flux diverter to minimize the axial short circuit force, in design stage of a sample 132/13.8 kV, 50 MVA three-phase core type HTS transformer. In this paper, the optimal dimensions, placement, and permeability of a flux diverter have been determined. It has been shown that utilizing this optimized flux diverter, the axial short circuit forces have been reduced significantly. Electromagnetic modeling and simulations, by the application of finite element method, have been employed for the verification of the analytical method results. A high degree of consistency has been observed between the analytical results and the simulation results.
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