dc.creatorMontoya O.D.
dc.creatorGarces A.
dc.creatorCastro C.A.
dc.date.accessioned2020-03-26T16:32:32Z
dc.date.accessioned2022-09-28T20:07:46Z
dc.date.available2020-03-26T16:32:32Z
dc.date.available2022-09-28T20:07:46Z
dc.date.created2020-03-26T16:32:32Z
dc.date.issued2018
dc.identifierIEEE Latin America Transactions; Vol. 16, Núm. 8; pp. 2213-2220
dc.identifier1548-0992
dc.identifierhttps://hdl.handle.net/20.500.12585/8874
dc.identifier10.1109/TLA.2018.8528237
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio UTB
dc.identifier56919564100
dc.identifier36449223500
dc.identifier56786626200
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3720353
dc.description.abstractIn this paper a mixed-integer non-linear programming formulation for optimal conductor selection in radial distribution networks is proposed. The objective function in this problem corresponds to the minimization of power losses and costs of investment in conductors. A typical set of constraints corresponding to the operative conditions in distribution systems, as power flow balance, voltage regulation, thermal capacity and telescopic conductors distribution, among others, are employed. Three different demand scenarios are considered to evaluate their impacts in the final conductor selection. The proposed mathematical model is solved using the general algebraic modeling system (GAMS) and DICOPT solver. Two radial distribution networks with 8 and 27 nodes, respectively, are employed to verify the general performance of the mathematical model proposed. © 2003-2012 IEEE.
dc.languageeng
dc.publisherIEEE Computer Society
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rightsAtribución-NoComercial 4.0 Internacional
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85056570979&doi=10.1109%2fTLA.2018.8528237&partnerID=40&md5=a980a6c2a27eb7b1b6c2819fd93ad908
dc.titleOptimal conductor size selection in radial distribution networks using a mixed-integer non-linear programming formulation


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