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dc.contributor.author
Mosteiro-Romero, Martín
dc.contributor.author
Hischier, Illias
dc.contributor.author
Fonseca, Jimeno A.
dc.contributor.author
Schlueter, Arno
dc.date.accessioned
2020-08-03T13:30:30Z
dc.date.available
2020-08-03T02:49:04Z
dc.date.available
2020-08-03T13:30:30Z
dc.date.issued
2020-08-15
dc.identifier.issn
0360-1323
dc.identifier.issn
0360-1323
dc.identifier.other
10.1016/j.buildenv.2020.107084
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/429612
dc.identifier.doi
10.3929/ethz-b-000429612
dc.description.abstract
District-scale building energy models can be a powerful tool for the integration of renewable energy sources and efficiency measures in urban areas. One key limitation of these models, however, has been their rather simplified treatment of building occupants. Since it is their activities which create the needs for energy in an area, an improved analysis of the effects of occupants on demand at the district scale is needed. This paper presents a novel population-based approach (PopAp) inspired by agent-based transportation models, in which a population of occupants was defined based on class and employee registers and each was given an individual daily schedule. This approach was then used to assess the effect of occupant presence modeling on district-scale energy demand simulations by comparing the data-centric PopAp method to standard-based deterministic and stochastic approaches. The maximum number of occupants in the area was found to be 33% higher for the deterministic model compared to the data-centric PopAp results, a deviation that was especially pronounced in education buildings. The results for space heating, space cooling and electricity demand for lighting and appliances show that while the mean deviation between models on a yearly basis is within 10% for all demands, on an hourly scale the deviation for space cooling and electricity exceeded 15%. Given the importance of the hourly scale for peak demand prediction for technology sizing, more detailed occupant modeling approaches should be considered when planning energy systems.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
Energy simulation
en_US
dc.subject
Urban building energy modeling
en_US
dc.subject
Building occupant modeling
en_US
dc.subject
Occupant presence models
en_US
dc.title
A novel population-based occupancy modeling approach for district-scale simulations compared to standard-based methods
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2020-07-09
ethz.journal.title
Building and Environment
ethz.journal.volume
181
en_US
ethz.pages.start
107084
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Oxford
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02602 - Inst. f. Technologie in der Architektur / Institute for Technology in Architecture::03902 - Schlüter, Arno / Schlüter, Arno
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02602 - Inst. f. Technologie in der Architektur / Institute for Technology in Architecture::03902 - Schlüter, Arno / Schlüter, Arno
ethz.date.deposited
2020-08-03T02:49:12Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-08-03T13:30:54Z
ethz.rosetta.lastUpdated
2022-03-29T02:44:44Z
ethz.rosetta.versionExported
true
ethz.COinS
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