Modelagem da capacitância de elementos magnéticos para elevadas frequências e classes de isolação

• Autor(a) principal: Chagas, Natalia Braun
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/001300000rh9m
• Texto Completo: http://repositorio.ufsm.br/handle/1/16588
• topic: Classe de isolação; Transformador de estado sólido; Redes inteligentes; Elemento finito; Insulation class; Solid state transformer; Smart grids; Finite elements; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

This PhD thesis presents the development of models of magnetic elements for high frequency and insulation classes. Currently, there is an increasing demand for implementation of such elements as the power electronics has innovated with the development of technologies capable of operating under such conditions, high frequency and voltage. Different applications such as smart grids, distributed generation connection and solid-state transformers boost research in this area. The main motivation of this study is to develop a model to emulate the magnetic element, both for electrical insulation design as to verify the interaction of the element with the electronic circuit in which it is inserted. The model was based on the techno-scientific literature dedicated to power transformers, which have high insulation classes, but do not operate at high frequency. A new method is proposed for calculating the value of the parasitic capacitance between conductors of circular cross-section. Design techniques with the objective of reducing the self-capacitance, or parasitic capacitance, are presented. Comparisons between experimental results and simulations of the proposed model are presented, proving its effectiveness. The proposed model is further expanded and applied if insulation material is required between the layers of the coils to raise its electrical insulation. In the same way, experimental tests are performed to prove the conclusions presented for this modeling.