dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorSilva, Irenio de J.
dc.creatorRider, Marcos J.
dc.creatorRomero, Ruben
dc.creatorMurari, Carlos A. F.
dc.date2014-05-20T15:25:57Z
dc.date2016-10-25T18:00:33Z
dc.date2014-05-20T15:25:57Z
dc.date2016-10-25T18:00:33Z
dc.date2006-11-01
dc.date.accessioned2017-04-05T23:55:01Z
dc.date.available2017-04-05T23:55:01Z
dc.identifierIEEE Transactions on Power Systems. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc., v. 21, n. 4, p. 1565-1573, 2006.
dc.identifier0885-8950
dc.identifierhttp://hdl.handle.net/11449/36264
dc.identifierhttp://acervodigital.unesp.br/handle/11449/36264
dc.identifier10.1109/TPWRS.2006.881159
dc.identifierWOS:000241839700011
dc.identifierhttp://dx.doi.org/10.1109/TPWRS.2006.881159
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/879824
dc.descriptionThis paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relationIEEE Transactions on Power Systems
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectdirect current (dc) model
dc.subjectgenetic algorithm
dc.subjectlong-term transmission network expansion planning
dc.subjectuncertainty in demand
dc.titleTransmission network expansion planning considering uncertainty in demand
dc.typeOtro


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