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Information integration and semantic interpretation for building energy system operation and maintenance

 
: Pruvost, Hervé; Enge-Rosenblatt, Olaf; Haufe, Jürgen

:
Postprint urn:nbn:de:0011-n-5160883 (1.7 MByte PDF)
MD5 Fingerprint: f895bf92b86c61a19f5d463dbc066e6f
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Erstellt am: 8.11.2018


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Industrial Electronics Society -IES-:
44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 : Washington D.C., USA, October 21-23, 2018
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5090-6684-1
S.813-818
IEEE Industrial Electronics Society (IECON Annual Conference) <44, 2018, Washington/DC>
Bundesministerium für Wirtschaft und Technologie BMWi
03ET1372A; FMopt
Verfahren zur Ressourcenminimierung im technischen Gebäudebetrieb. Teilvorhaben: Modellentwicklung und Optimierung
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IIS, Institutsteil Entwurfsautomatisierung (EAS) ()

Abstract
Digitalization in facility management has become an active field of research for many reasons. Among others, it can provide high support by saving energy and cost in the building sector as well as for optimizing internal processes involved within the management of a facility. To enable this, many data about a building has to be collected and analyzed. Building management systems can already produce huge amounts of data that are analyzed for supervising, controlling and benchmarking buildings. However, even if numerous data are produced during building operation there is no much use of building information created during its design. In view of that, this research proposes a methodology and a software framework for closing the informational gaps between building design and operation. It follows data integration steps that use initial building information models and extend them with operation data as well as semantic models. These data models are used for interpreting energy system behaviors and performing predictive analyses. More specifically, a system ontology is introduced that supports reuse of knowledge for optimized building operation and maintenance.

: http://publica.fraunhofer.de/dokumente/N-516088.html