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dc.creatorBejarano Pellicer, Guillermoes
dc.creatorLemos, Joao M.es
dc.creatorRico-Azagra, Javieres
dc.creatorRodríguez Rubio, Franciscoes
dc.creatorOrtega Linares, Manuel Giles
dc.date.accessioned2023-01-19T10:16:09Z
dc.date.available2023-01-19T10:16:09Z
dc.date.issued2022-09-02
dc.identifier.citationBejarano Pellicer, G., Lemos, J.M., Rico-Azagra, J., Rodríguez Rubio, F. y Ortega Linares, M.G. (2022). Energy management of refrigeration systems with thermal energy storage based on non-linear model predictive control. Mathematics, 10 (17), 3167. https://doi.org/10.3390/math10173167.
dc.identifier.issn2227-7390es
dc.identifier.urihttps://hdl.handle.net/11441/141572
dc.description.abstractThis work addresses the energy management of a combined system consisting of a refrigeration cycle and a thermal energy storage tank based on phase change materials. The storage tank is used as a cold-energy buffer, thus decoupling cooling demand and production, which leads to cost reduction and satisfaction of peak demand that would be infeasible for the original cycle. A layered scheduling and control strategy is proposed, where a non-linear predictive scheduler computes the references of the main powers involved (storage tank charging/discharging powers and direct cooling production), while a low-level controller ensures that the requested powers are actually achieved. A simplified model retaining the dominant dynamics is proposed as the prediction model for the scheduler. Economic, efficiency, and feasibility criteria are considered, seeking operating cost reduction while ensuring demand satisfaction. The performance of the proposed strategy for the system with energy storage is compared in simulation with that of a cycle without energy storage, where the former is shown to satisfy challenging demands while reducing the operating cost by up to 28%. The proposed approach also shows suitable robustness when significant uncertainty in the prediction model is considered.es
dc.formatapplication/pdfes
dc.format.extent27 p.es
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofMathematics, 10 (17), 3167.
dc.rightsAn error occurred on the license name.*
dc.rights.uriAn error occurred getting the license - uri.*
dc.subjectRefrigeration systemes
dc.subjectThermal energy storagees
dc.subjectPhase change materialses
dc.subjectNon-linear model predictive controles
dc.subjectSchedulinges
dc.titleEnergy management of refrigeration systems with thermal energy storage based on non-linear model predictive controles
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería de Sistemas y Automáticaes
dc.relation.projectIDRTI2018-101897-B-I00es
dc.relation.publisherversionhttps://www.mdpi.com/2227-7390/10/17/3167es
dc.identifier.doi10.3390/math10173167es
dc.contributor.groupUniversidad de Sevilla. TEP201: Ingeniería de automatización, control y robóticaes
idus.validador.notaThis article is an open access article, Creative Commons Attribution (CC BY) licensees
dc.journaltitleMathematicses
dc.publication.volumen10es
dc.publication.issue17es
dc.publication.initialPage3167es
dc.contributor.funderAgencia Estatal de Investigación. Españaes
dc.contributor.funderEuropean Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)es

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