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dc.contributor.author
Eichler, Annika
dc.contributor.author
Darivianakis, Georgios
dc.contributor.author
Lygeros, John
dc.contributor.editor
Dochain, Denis
dc.contributor.editor
Henrion, Didier
dc.contributor.editor
Peaucelle, Dimitri
dc.date.accessioned
2021-07-28T06:21:34Z
dc.date.available
2018-01-22T11:04:11Z
dc.date.available
2018-01-23T11:52:16Z
dc.date.available
2018-01-23T12:22:16Z
dc.date.available
2018-09-11T13:53:57Z
dc.date.available
2021-07-28T06:21:34Z
dc.date.issued
2017-07
dc.identifier.issn
2405-8963
dc.identifier.other
10.1016/j.ifacol.2017.08.2295
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/232152
dc.description.abstract
Efficient building energy management has attracted a great deal of academic interest with significant potential energy savings to be envisaged. Social scientists strive to achieve these savings by employing behavior-based approaches, while engineers investigate control strategies for the efficient operation of the building devices. This work can be seen as a first step towards bridging these two approaches by proposing a control scheme that encapsulates building occupant behavior into the energy management system. In particular, the occupants willingness to tolerate comfort bound violations is modeled as a random measurable uncertainty and incorporated into the building energy management system through disturbance feedback control policies. The respective optimal control problem is formulated as a mixed-integer stochastic optimization problem, and a computationally tractable approximation of it is derived by restricting the disturbance feedback control policies to admit an affine structure. An extensive numerical study verifies that the proposed approach can significantly reduce the energy consumption of the buildings.
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
building automation
en_US
dc.subject
computational social sciences
en_US
dc.subject
robust control
en_US
dc.subject
convex optimization
en_US
dc.subject
predictive control
en_US
dc.subject
humans-in-the-loop
en_US
dc.title
Humans in the loop: A stochastic predictive approach to building energy management in the presence of unpredictable users
en_US
dc.type
Conference Paper
dc.date.published
2017-10-18
ethz.book.title
20th IFAC World Congress. Proceedings
en_US
ethz.journal.title
IFAC-PapersOnLine
ethz.journal.volume
50
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
14471
en_US
ethz.pages.end
14476
en_US
ethz.event
20th IFAC World Congress (IFAC 2017)
en_US
ethz.event.location
Toulouse, France
en_US
ethz.event.date
July 9-14, 2017
en_US
ethz.publication.place
Kidlington
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
ethz.date.deposited
2018-01-22T11:04:12Z
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-01-23T11:52:21Z
ethz.rosetta.lastUpdated
2022-03-29T10:45:17Z
ethz.rosetta.versionExported
true
ethz.COinS
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