dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T19:51:41Z
dc.date.accessioned2022-12-19T20:19:27Z
dc.date.available2020-12-10T19:51:41Z
dc.date.available2022-12-19T20:19:27Z
dc.date.created2020-12-10T19:51:41Z
dc.date.issued2018-01-01
dc.identifierProceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la). New York: Ieee, 5 p., 2018.
dc.identifier2381-3571
dc.identifierhttp://hdl.handle.net/11449/196648
dc.identifierWOS:000518200300055
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5377285
dc.description.abstractThe optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.
dc.languageeng
dc.publisherIeee
dc.relationProceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la)
dc.sourceWeb of Science
dc.subjectBiased random-key genetic algorithm
dc.subjectelectrical distribution systems
dc.subjectpower losses
dc.subjectreconfiguration
dc.titleBiased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
dc.typeActas de congresos


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