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dc.contributor.authorGiretti, Aen
dc.contributor.authorVaccarini, Men
dc.contributor.authorCasals, Men
dc.contributor.authorMacarulla, Men
dc.contributor.authorFuertes, Aen
dc.contributor.authorJones, RVen
dc.date.accessioned2018-03-09T14:33:48Z
dc.date.available2018-03-09T14:33:48Z
dc.date.issued2018-05-15en
dc.identifier.issn0378-7788en
dc.identifier.urihttp://hdl.handle.net/10026.1/11042
dc.description.abstract

Buildings subject to Energy Performance Contracts (EPCs) are usually quite complex public buildings, sometimes relatively old and usually barely documented from the technical standpoint. Gathering comprehensive and reliable technical information is a time consuming and expensive process that has to be carried out within the submission deadline. In these conditions, the standard approach to energy performance forecasting which uses detailed simulation is practically unfeasible. This paper proposes a reduced-order modeling approach that is tailored to the EPC tendering phase. The proposed methodology extends a third order building model, introducing explicit, albeit still abstract, representations of the heating/cooling system, of the weather influence and of the end-user gains. The extended parameter set reflects to a large degree the information that is readily available in practical on-site surveying, or that can be easily calculated from that information. As a consequence of the simplified physics, a knowledge driven, practical calibration procedure, which provides an effective way of reducing uncertainty, is proposed. The calibration procedure analyses the uncertainty present in the available knowledge and uses the constraints imposed by the implemented physics on the parameters’ dynamic to assess their value estimation. The modeling approach is exemplified through three case studies: the first one provides the comparison of the reduced-order model predictions with the outcomes of a detailed model of a small hospital, the second one is used to compare the reduced-order model predictions with the detailed measurements of energy consumption of a real building, and the third case study exemplifies the use in operational context with scarce information.

en
dc.format.extent216 - 230en
dc.language.isoenen
dc.publisherElsevieren
dc.subjectReduced-order modelingen
dc.subjectEnergy performance contractingen
dc.subjectModel calibrationen
dc.subjectThermal modelingen
dc.titleReduced-order Modeling for Energy Performance Contractingen
dc.typeJournal Article
plymouth.volume167en
plymouth.publisher-urlhttps://www.sciencedirect.com/science/article/pii/S0378778817337799en
plymouth.publication-statusAccepteden
plymouth.journalEnergy and Buildingsen
dc.identifier.doi10.1016/j.enbuild.2018.02.049en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business
plymouth.organisational-group/Plymouth/Faculty of Arts, Humanities and Business/School of Art, Design and Architecture
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA13 Architecture, Built Environment and Planning
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2018-02-25en
dc.rights.embargodate2019-03-01en
dc.rights.embargoperiodNot knownen
rioxxterms.versionAMen
rioxxterms.versionofrecord10.1016/j.enbuild.2018.02.049en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-05-15en
rioxxterms.typeJournal Article/Reviewen


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