Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/67990

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dc.contributor.authorMontero-Sousa, Juan Aureliopor
dc.contributor.authorAláiz-Moretón, Héctorpor
dc.contributor.authorQuintián, Héctorpor
dc.contributor.authorGonzález-Ayuso, Tomáspor
dc.contributor.authorNovais, Paulopor
dc.contributor.authorCalvo-Rolle, José Luispor
dc.date.accessioned2020-11-03T16:45:44Z-
dc.date.available2020-11-03T16:45:44Z-
dc.date.issued2020-
dc.identifier.issn0360-5442-
dc.identifier.urihttps://hdl.handle.net/1822/67990-
dc.description.abstractEnergy storage is one of the challenges of the electric sector. There are several different technologies available for facing it, from the traditional ones to the most advanced. With the current trend, it is mandatory to develop new energy storage systems that allow optimal efficiency, something that does not happen with traditional ones. Another feature that new systems must meet is to envisage the behaviour of energy generation and consumption. With this aim, the present research deals the hydrogen consumption prediction of a fuel cell based system thanks a hybrid intelligent approach implementation. The work is based on a real testing plant. Two steps have been followed to create a hybrid model. First, the real dataset has been divided into groups whose elements have similar characteristics. The second step, carry out the regression using different techniques. Very satisfactory results have been achieved during the validation of the model.por
dc.description.sponsorship- (undefined)por
dc.language.isoengpor
dc.publisherElsevier Ltdpor
dc.rightsopenAccesspor
dc.subjectANNpor
dc.subjectBHLpor
dc.subjectEnergy managementpor
dc.subjectEnergy storagepor
dc.subjectFuel cellpor
dc.subjectSVMpor
dc.titleHydrogen consumption prediction of a fuel cell based system with a hybrid intelligent approachpor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0360544220310938por
oaire.citationVolume205por
dc.date.updated2020-11-03T15:00:30Z-
dc.identifier.doi10.1016/j.energy.2020.117986por
dc.subject.wosScience & Technology-
sdum.export.identifier7468-
sdum.journalEnergypor
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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