Metodologia de detecção e classificação de faltas de alta impedância em redes de distribuição: implementação em hardware e validação por meio de simulação digital em tempo real
Ano de defesa: | 2020 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
Brasil Engenharia Elétrica UFSM Programa de Pós-Graduação em Engenharia Elétrica Centro de Tecnologia |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/22445 |
Resumo: | The present work deals with the detection of high impedance faults (HIF) in Electricity Distribution Networks. An in-depth study is carried out on this type of fault, as well as on some important HIF detection methods. From this analysis, a HIF detection and classification method is developed. An important feature of the proposed methodology is the fact that it is able to identify the type of HIF, i.e., with or without a cable break, for instance. The developed algorithm is based on harmonic components, mainly the third order. To extract information about faults, phase and neutral currents are used. In order to carry out a comparative analysis, the proposed algorithm and other four known methods of HIF detection were implemented in a hardware platform developed for this purpose. All tests were performed in real time using hardware-in-the-loop simulation through OPAL-RT simulator. In total, 774 tests were performed for each algorithm, including two HIF models with different soil topologies and broken cable configuration. Transformer inrush, load switching and capacitor bank cases were also tested. The simulations of all cases were carried out through a distribution system based on a real feeder, which has, as main characteristic, the presence of single-phase branches. The developed methodology has presented a superior result when compared to the other methods, showing an assertiveness of 88% in the cases of HIF. |