Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17807
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dc.contributor.authorXue, Xen_US
dc.contributor.authorWang, Sen_US
dc.contributor.authorSun, Yen_US
dc.contributor.authorXiao, Fen_US
dc.date.accessioned2014-12-19T07:11:43Z-
dc.date.available2014-12-19T07:11:43Z-
dc.date.issued2014-
dc.identifier.citationApplied energy, 2014, v. 116, p. 297-310en_US
dc.identifier.issn0306-2619-
dc.identifier.urihttp://hdl.handle.net/10397/17807-
dc.description.abstractWith increasing use and integration of renewable energies, power imbalance between supply and demand sides has become one of the most critical issues in developing smart grid. As the major power consumers at demand side, buildings can actually perform as distributed thermal storages to help relieving power imbalance of a grid. However, power demand alteration potentials of buildings and energy information of grids might not be effectively predicted and communicated for interaction and optimization. This paper presents an interactive building power demand management strategy for the interaction of commercial buildings with a smart grid and facilitating the grid optimization. A simplified building thermal storage model is developed for predicting and characterizing power demand alteration potentials of individual buildings together with a model for predicting the normal power demand profiles of buildings. The simulation test results show that commercial buildings can contribute significantly and effectively in power demand management or alterations with building power demand characteristics identified properly.en_US
dc.description.sponsorshipDepartment of Building Services Engineeringen_US
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.relation.ispartofApplied energyen_US
dc.subjectBuilding demand managementen_US
dc.subjectBuilding thermal storage modelen_US
dc.subjectDynamic pricingen_US
dc.subjectInteractive strategyen_US
dc.subjectSmart griden_US
dc.titleAn interactive building power demand management strategy for facilitating smart grid optimizationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage297-
dc.identifier.epage310-
dc.identifier.volume116-
dc.identifier.doi10.1016/j.apenergy.2013.11.064-
dc.identifier.scopus2-s2.0-84890815228-
dc.identifier.eissn1872-9118-
dc.identifier.rosgroupidr71178-
dc.description.ros2013-2014 > Academic research: refereed > Publication in refereed journal-
Appears in Collections:Journal/Magazine Article
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