<div class="csl-bib-body">
<div class="csl-entry">Bratukhin, A., Stippel, C., Sengl, D., Kobelrausch, M. D., & Sauter, T. (2024). Energy Efficiency Optimization and Preventive Maintenance of HVAC Systems Using Machine Learning. In IEEE Xplore (Ed.), <i>2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)</i>. https://doi.org/10.1109/ETFA61755.2024.10710735</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/209778
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dc.description.abstract
HVAC systems are characterized by rigid and complex internal behaviour that limits the options for efficiency optimization. KI4HVACs project aims to apply machine learning to improve office building HVAC operation and maintenance efficiency. Reinforcement learning is used for energy use optimization and supervised learning for preventive maintenance. The models are wrapped into an MPC based and a decision tree algorithm for preventive maintenance. The system uses the TRNSYS18 simulation environment that matches an actual office building with multiple zones.
en
dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.subject
energy consumption
en
dc.subject
energy modelling
en
dc.subject
HVAC
en
dc.subject
machine learning
en
dc.title
Energy Efficiency Optimization and Preventive Maintenance of HVAC Systems Using Machine Learning
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Universität für Weiterbildung Krems, Austria
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dc.relation.isbn
979-8-3503-6123-0
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dc.relation.doi
10.1109/ETFA61755.2024
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dc.relation.grantno
888448
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dc.type.category
Full-Paper Contribution
-
tuw.booktitle
2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)
-
tuw.peerreviewed
true
-
tuw.project.title
Energieeffizienzoptimierung von HLK-Systemen durch prädiktiver Algorithmen und Modellbildung mittels maschinellem Lernen
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tuw.researchTopic.id
E1
-
tuw.researchTopic.id
C5
-
tuw.researchTopic.id
C6
-
tuw.researchTopic.name
Energy Active Buildings, Settlements and Spatial Infrastructures
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tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.name
Modeling and Simulation
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tuw.researchTopic.value
50
-
tuw.researchTopic.value
25
-
tuw.researchTopic.value
25
-
tuw.publication.orgunit
E384-02 - Forschungsbereich Systems on Chip
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tuw.publication.orgunit
E384-01 - Forschungsbereich Software-intensive Systems
-
tuw.publication.orgunit
E193-01 - Forschungsbereich Computer Vision
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tuw.publisher.doi
10.1109/ETFA61755.2024.10710735
-
dc.description.numberOfPages
4
-
tuw.author.orcid
0009-0005-4472-4750
-
tuw.author.orcid
0000-0003-1559-8394
-
tuw.event.name
2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)
en
tuw.event.startdate
10-09-2024
-
tuw.event.enddate
13-09-2024
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Padova
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tuw.event.country
IT
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tuw.event.presenter
Sauter, Thilo
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wb.sciencebranch
Elektrotechnik, Elektronik, Informationstechnik
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wb.sciencebranch.oefos
2020
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wb.sciencebranch.value
100
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dc.contributor.editorgroup
IEEE Xplore
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item.fulltext
no Fulltext
-
item.languageiso639-1
en
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.cerifentitytype
Publications
-
item.grantfulltext
none
-
item.openairetype
conference paper
-
crisitem.project.funder
FFG - Österr. Forschungsförderungs- gesellschaft mbH
-
crisitem.project.grantno
888448
-
crisitem.author.dept
E384-01 - Forschungsbereich Software-intensive Systems
-
crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
-
crisitem.author.dept
E384-02 - Forschungsbereich Systems on Chip
-
crisitem.author.dept
E384 - Institut für Computertechnik
-
crisitem.author.orcid
0000-0003-1559-8394
-
crisitem.author.parentorg
E384 - Institut für Computertechnik
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
crisitem.author.parentorg
E384 - Institut für Computertechnik
-
crisitem.author.parentorg
E350 - Fakultät für Elektrotechnik und Informationstechnik
