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dc.contributor.authorEscoto, Esau Figueroa [UNESP]
dc.contributor.authorLeao, Fabio Bertequini [UNESP]
dc.date.accessioned2020-12-12T01:21:06Z
dc.date.available2020-12-12T01:21:06Z
dc.date.issued2019-11-01
dc.identifierhttp://dx.doi.org/10.1109/ROPEC48299.2019.9057099
dc.identifier.citation2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019.
dc.identifier.urihttp://hdl.handle.net/11449/198752
dc.description.abstractA new method, based on binary integer programming, to solve the problem of fault section estimation in power systems is developed in this work. This optimization model is formulated based on a set of minimum covers, subject to logical protection constraints applied by electric power companies. Constraints of this formulation, compares protection relay alarms reported from the SCADA system with the expected states of the protection relay functions allocated in power system. Naturally, the proposed problem is a complex binary integer nonlinear programming model. In order to apply classical optimization techniques, this model is recast as binary integer linear programming model. Numerical results show the effectiveness, applicability and robustness of the presented strategy by using a 7-bus test system.en
dc.language.isoeng
dc.relation.ispartof2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019
dc.sourceScopus
dc.subjectElectrical power Systems
dc.subjectFault diagnosis
dc.subjectFault section estimation
dc.subjectInteger programming
dc.subjectMathematical programming
dc.titleA binary integer linear programming model for fault section estimation in electric power systemsen
dc.typeTrabalho apresentado em evento
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.description.affiliationSão Paulo State University (Unesp) Department of Electrical Engineering
dc.description.affiliationUnespSão Paulo State University (Unesp) Department of Electrical Engineering
dc.identifier.doi10.1109/ROPEC48299.2019.9057099
dc.identifier.scopus2-s2.0-85083579677
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