dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2019-10-06T16:56:08Z | |
dc.date.accessioned | 2022-12-19T19:00:29Z | |
dc.date.available | 2019-10-06T16:56:08Z | |
dc.date.available | 2022-12-19T19:00:29Z | |
dc.date.created | 2019-10-06T16:56:08Z | |
dc.date.issued | 2018-10-26 | |
dc.identifier | Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018. | |
dc.identifier | http://hdl.handle.net/11449/189908 | |
dc.identifier | 10.1109/TDC-LA.2018.8511718 | |
dc.identifier | 2-s2.0-85057015390 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5370946 | |
dc.description.abstract | The 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.language | eng | |
dc.relation | Proceedings of the 2018 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D-LA 2018 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Biased random-key genetic algorithm | |
dc.subject | electrical distribution systems | |
dc.subject | power losses | |
dc.subject | reconfiguration | |
dc.title | Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems | |
dc.type | Actas de congresos | |