Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3592
DC FieldValueLanguage
dc.contributor.authorFreund, Svenne-
dc.contributor.authorSchmitz, Gerhard-
dc.date.accessioned2021-06-10T11:11:01Z-
dc.date.available2021-06-10T11:11:01Z-
dc.date.issued2021-03-27-
dc.identifier.citationBuilding and Environment 197: 107830 (2021-06-15)de_DE
dc.identifier.issn0360-1323de_DE
dc.identifier.urihttp://hdl.handle.net/11420/9719-
dc.description.abstractModern and energy-optimized buildings often lack an intelligent and advanced control strategy. Instead, conventional rule-based control (RBC) strategies are still mainly used today, which do not exploit the full performance potential of these buildings. Model predictive control (MPC) has proven in simulation studies and pilot cases to be a promising approach to reduce the energy consumption of buildings, while improving occupants’ comfort. However, there is still a lack of implementing MPC in real, large-scale and fully occupied buildings, to further prove this potential in real building operations. This paper describes the implementation and operation of MPC in a large-sized, low-energy office building. The MPC controller was implemented in a section of the building during a three-month test period from February to April 2020, controlling the supply temperature of heating circuits for thermally activated building systems (TABS). Its performance was compared to the default rule-based control which is active in the other building sections. This allows for a detailed evaluation of MPC versus RBC under identical environmental and operational conditions. The MPC controlled building section used 30% less heating energy than RBC controlled building sections, while the existing high level of thermal comfort could be maintained. Especially in transition periods (i. e. interseasonal periods like late winter/early spring), the MPC is superior to the conventional heating-curve based control strategy, with heating energy savings of 75%.en
dc.language.isodede_DE
dc.publisherElsevierde_DE
dc.relation.ispartofBuilding and environmentde_DE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de_DE
dc.subjectField testde_DE
dc.subjectModel predictive controlde_DE
dc.subjectModelicade_DE
dc.subjectOptimizationde_DE
dc.subjectThermally activated building system (TABS)de_DE
dc.subject.ddc600: Technikde_DE
dc.titleImplementation of model predictive control in a large-sized, low-energy office buildingde_DE
dc.typeArticlede_DE
dc.identifier.doi10.15480/882.3592-
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.0137560-
tuhh.oai.showtruede_DE
tuhh.abstract.englishModern and energy-optimized buildings often lack an intelligent and advanced control strategy. Instead, conventional rule-based control (RBC) strategies are still mainly used today, which do not exploit the full performance potential of these buildings. Model predictive control (MPC) has proven in simulation studies and pilot cases to be a promising approach to reduce the energy consumption of buildings, while improving occupants’ comfort. However, there is still a lack of implementing MPC in real, large-scale and fully occupied buildings, to further prove this potential in real building operations. This paper describes the implementation and operation of MPC in a large-sized, low-energy office building. The MPC controller was implemented in a section of the building during a three-month test period from February to April 2020, controlling the supply temperature of heating circuits for thermally activated building systems (TABS). Its performance was compared to the default rule-based control which is active in the other building sections. This allows for a detailed evaluation of MPC versus RBC under identical environmental and operational conditions. The MPC controlled building section used 30% less heating energy than RBC controlled building sections, while the existing high level of thermal comfort could be maintained. Especially in transition periods (i. e. interseasonal periods like late winter/early spring), the MPC is superior to the conventional heating-curve based control strategy, with heating energy savings of 75%.de_DE
tuhh.publisher.doi10.1016/j.buildenv.2021.107830-
tuhh.publication.instituteTechnische Thermodynamik M-21de_DE
tuhh.identifier.doi10.15480/882.3592-
tuhh.type.opus(wissenschaftlicher) Artikel-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.volume197de_DE
dc.rights.nationallicensefalsede_DE
dc.identifier.scopus2-s2.0-85105263060de_DE
tuhh.container.articlenumber107830de_DE
local.status.inpressfalsede_DE
local.type.versionpublishedVersionde_DE
item.languageiso639-1de-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.creatorOrcidFreund, Svenne-
item.creatorOrcidSchmitz, Gerhard-
item.mappedtypeArticle-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.creatorGNDFreund, Svenne-
item.creatorGNDSchmitz, Gerhard-
crisitem.author.deptTechnische Thermodynamik M-21-
crisitem.author.deptTechnische Thermodynamik-
crisitem.author.orcid0000-0003-1716-8136-
crisitem.author.orcid0000-0002-6702-5929-
crisitem.author.parentorgStudiendekanat Maschinenbau-
crisitem.author.parentorgStudiendekanat Maschinenbau-
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