Show simple item record

dc.contributor.authorSun, Y
dc.contributor.authorSilva, Elisabete
dc.contributor.authorTian, W
dc.contributor.authorChoudhary, Ruchi
dc.contributor.authorLeng, H
dc.date.accessioned2018-12-14T00:31:40Z
dc.date.available2018-12-14T00:31:40Z
dc.date.issued2018-11
dc.identifier.issn2071-1050
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/286928
dc.description.abstract<jats:p>In this paper, we developed a new integrated analysis environment in order to thoroughly analyses urban-building energy patterns, named IUBEA (integrated urban building energy analysis), which focuses on energy modeling and analysis of a city’s building stock to support district or city-scale efficiency programs. It is argued that cities and towns account for more than two-thirds of world energy consumption. Thus, this paper explores techniques to integrate a spatial analysis environment in the field of urban building energy assessment in cites to make full use of current spatial data relevant to urban-building energy consumption and energy efficiency policies. We illustrate how multi-scale sampling and analysis for energy consumption and simulate the energy-saving scenarios by taking as an example of Greater London. In the final part, is an application of an agent-based model (ABM) in IUBEA regarding behavioral and economic characteristics of building stocks in the context of building energy efficiency. This paper first describes the basic concept for this integrated spatial analysis environment IUBEA. Then, this paper discusses the main functions for this new environment in detail. The research serves a new paradigm of the multi-scale integrated analysis that can lead to an efficient energy model, which contributes the body of knowledge of energy modeling beyond the single building scale. Findings also proved that ABM is a feasible tool to tackle intellectual challenges in energy modeling. The final adoption example of Greater London demonstrated that the integrated analysis environment as a feasible tool for building energy consumption have unique advantages and wide applicability.</jats:p>
dc.publisherMDPI AG
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleAn integrated spatial analysis computer environment for urban-building energy in cities
dc.typeArticle
prism.issueIdentifier11
prism.publicationDate2018
prism.publicationNameSustainability (Switzerland)
prism.volume10
dc.identifier.doi10.17863/CAM.34237
dcterms.dateAccepted2018-11-15
rioxxterms.versionofrecord10.3390/su10114235
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-11-16
dc.contributor.orcidSilva, Elisabete [0000-0002-5816-6447]
dc.identifier.eissn2071-1050
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/N021614/1)
pubs.funder-project-idTechnology Strategy Board (920035)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/K000314/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/L010917/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/F034350/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/I019308/1)
cam.issuedOnline2018-11-16


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International