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dc.contributor.authorPéan, Thibaut
dc.contributor.authorSalom Tormo, Jaume
dc.contributor.authorCosta Castelló, Ramon
dc.contributor.otherInstitut de Recerca en Energía de Catalunya
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2019-01-25T12:50:27Z
dc.date.available2019-01-25T12:50:27Z
dc.date.issued2018
dc.identifier.citationPéan, T.; Salom, J.; Costa-Castelló, R. Configurations of model predictive control to exploit energy flexibility in building thermal loads. A: IEEE Conference on Decision and Control. "2018 IEEE Conference on Decision and Control (CDC)". IEEE Press, 2018, p. 3177-3182.
dc.identifier.urihttp://hdl.handle.net/2117/127600
dc.description© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractA model predictive control (MPC) framework is developed in the present study, with the final objective to improve the energy flexibility of building thermal loads through demand-side management. Three different configurations are tested and tuned, with the following objective functions: minimizing the delivered energy to the building, the electrical energy used by the HVAC system (heat pump) or the cost of this electricity use. To validate these MPC configurations, a Matlab-Trnsys co-simulator is also created, in order to run the MPC on a virtual plant composed of a detailed building model. The MPC strategy manages to run effectively on the chosen study case (a residential building with heat pump in Spain), and the differences between configurations are discussed.
dc.format.extent6 p.
dc.language.isoeng
dc.publisherIEEE Press
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.othercontrol theory
dc.subject.otheroptimal control
dc.titleConfigurations of model predictive control to exploit energy flexibility in building thermal loads
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
dc.identifier.doi10.1109/CDC.2018.8619452
dc.description.peerreviewedPeer Reviewed
dc.subject.inspecClassificació INSPEC::Control theory
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8619452
dc.rights.accessOpen Access
drac.iddocument23635835
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/675318/EU/Innovative controls for renewable sources Integration into smart energy systems/INCITE
upcommons.citation.authorPéan, T.; Salom, J.; Costa-Castelló, R.
upcommons.citation.contributorIEEE Conference on Decision and Control
upcommons.citation.publishedtrue
upcommons.citation.publicationName2018 IEEE Conference on Decision and Control (CDC)
upcommons.citation.startingPage3177
upcommons.citation.endingPage3182


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