<div class="csl-bib-body">
<div class="csl-entry">Fenz, S., Giannakis, G., Bergmayr, J., & Iousef, S. (2023). RenoDSS - a BIM-based building renovation decision support system. <i>Energy and Buildings</i>, Article 112999. https://doi.org/10.1016/j.enbuild.2023.112999</div>
</div>
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dc.identifier.issn
0378-7788
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/175983
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dc.description.abstract
Increasing the building renovation rate is a key initiative to drive energy efficiency in the sector and contribute to the European Green Deal. Within this paper, the BIM-based building renovation decision support system RenoDSS is described. RenoDSS (i) automatically generates renovation scenarios based on user preferences and the IFC representation (including second level space boundaries data) of the current building configuration (baseline), (ii) calculates baseline and renovation scenario KPIs, and (iii) identifies the most suitable scenarios by comparing the scenarios’ energy, finance, and sustainability KPIs. Validation conducted at two pilot sites shows that RenoDSS reduces the time for (i) identifying potential renovation scenarios, (ii) calculating their energy and LCA/LCC KPIs, and (iii) producing an IFC file for each renovation scenario by around 80% compared to tool-supported manual means. RenoDSS is used by (i) renovation designers that want to optimize the thermal building hull in combination with PV, solar thermal, and HVAC, as well as (ii) decision makers who want to collaboratively identify the most promising renovation option out of the ones generated by RenoDSS.
en
dc.language.iso
en
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dc.publisher
ELSEVIER SCIENCE SA
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dc.relation.ispartof
Energy and Buildings
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dc.subject
building renovation planning
en
dc.subject
decision support system
en
dc.subject
energy efficiency
en
dc.subject
building information modeling
en
dc.title
RenoDSS - a BIM-based building renovation decision support system
en
dc.type
Article
en
dc.type
Artikel
de
dc.contributor.affiliation
Eindhoven University of Technology, Netherlands (the)
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dcterms.dateSubmitted
2023-01-16
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dc.type.category
Original Research Article
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
-
wb.publication.intCoWork
International Co-publication
-
tuw.researchTopic.id
I4a
-
tuw.researchTopic.name
Information Systems Engineering
-
tuw.researchTopic.value
100
-
dcterms.isPartOf.title
Energy and Buildings
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publisher.doi
10.1016/j.enbuild.2023.112999
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dc.date.onlinefirst
2023-03-24
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dc.identifier.articleid
112999
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dc.identifier.eissn
1872-6178
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dc.description.numberOfPages
49
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tuw.author.orcid
0000-0003-2157-1534
-
tuw.author.orcid
0000-0002-1138-3444
-
wb.sci
true
-
wb.sciencebranch
Informatik
-
wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
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wb.sciencebranch.value
90
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wb.sciencebranch.value
10
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item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
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item.openairetype
research article
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item.fulltext
no Fulltext
-
item.languageiso639-1
en
-
item.grantfulltext
none
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item.cerifentitytype
Publications
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.dept
Eindhoven University of Technology
-
crisitem.author.orcid
0000-0002-2880-1526
-
crisitem.author.orcid
0000-0003-2157-1534
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crisitem.author.orcid
0000-0002-1138-3444
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering