dc.contributorCardoso Junior, Ghendy
dc.contributorhttp://lattes.cnpq.br/6284386218725402
dc.contributorMorais, Adriano Peres de
dc.contributorhttp://lattes.cnpq.br/2780595038162903
dc.contributorOliveira, Aécio de Lima
dc.contributorhttp://lattes.cnpq.br/3513022402512752
dc.contributorMarchesan, Gustavo
dc.contributorhttp://lattes.cnpq.br/4254867243649147
dc.contributorBretas, Arturo Suman
dc.contributorhttp://lattes.cnpq.br/1115674574513907
dc.contributorMoreto, Miguel
dc.contributorhttp://lattes.cnpq.br/4853832668516720
dc.creatorFarias, Patrick Escalante
dc.date.accessioned2018-08-08T17:49:05Z
dc.date.accessioned2019-05-24T20:27:46Z
dc.date.available2018-08-08T17:49:05Z
dc.date.available2019-05-24T20:27:46Z
dc.date.created2018-08-08T17:49:05Z
dc.date.issued2017-06-30
dc.identifierhttp://repositorio.ufsm.br/handle/1/14035
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2841282
dc.description.abstractThis work proposes a time-domain methodology to locate high impedance faults in overhead distribution systems. One of the innovative aspects of the method is the proposition of a single mathematical model to represent the different V x I curves generated during a high impedance fault in different types of soils. The feeder behavior is modeled by the distance of the fault, the network parameters and the currents and voltages measured at the substation. Therefore, the proposed method does not require the installation of any additional measurement equipment in the network. The feeder capacitances were also considered in the system model, making it closer to a real feeder. Another innovative aspect is the use of an artificial neural network to estimate the unknown parameters of the nonlinear equations that model the feeder behavior during high impedance faults. This network is trained continuously, and only after the fault starts, through the data generated by the own fault. Thus, it is not necessary to simulate several cases for the previous training of the network. The performance of the proposed method was evaluated in IEEE 34 node test feeder through the variation of soil type, fault incidence angles and load feeder. Furthermore, the influence of the current estimation methodology on the fault point was also evaluated. Finally, the performance of the method proposed was compared with another article recently presented. In general, in 86% of the cases tested, the algorithm obtained an error less than 2.5% in the estimation of the fault distance, and the maximum error obtained was 4%. In the comparative analysis with the other method, the proposed algorithm obtained better results in all cases tested, regardless of the soil type in which the fault occurred and its distance. The good results obtained, combined with its simplicity and low cost of implementation, make the method proposed in this work promising for the application in a real feeder.
dc.publisherUniversidade Federal de Santa Maria
dc.publisherBrasil
dc.publisherEngenharia Elétrica
dc.publisherUFSM
dc.publisherPrograma de Pós-Graduação em Engenharia Elétrica
dc.publisherCentro de Tecnologia
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.subjectLocalização de faltas
dc.subjectCurtos-circuitos
dc.subjectAlta impedância de falta
dc.subjectRedes neurais
dc.subjectTreinamento continuo
dc.subjectTensão no ponto de falta
dc.subjectFault location
dc.subjectShort circuits
dc.subjectHigh impedance fault
dc.subjectNeural networks
dc.subjectContinuous training
dc.subjectVoltage at the Fault point
dc.titleMétodo para estimação da distância de faltas de alta impedância em redes de distribuição de energia elétrica considerando diferentes tipos de solo
dc.typeTese


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