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Article: Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

TitleDeveloping a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate
Authors
KeywordsCalibration
CityBEUM
High spatiotemporal resolution
Urban building energy use
Issue Date2018
Citation
Building and Environment, 2018, v. 136, p. 107-117 How to Cite?
AbstractUrban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa, U.S. First, 28 commercial and 6 residential building prototypes were designed by combining Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S. Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal patterns of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.
Persistent Identifierhttp://hdl.handle.net/10722/329501
ISSN
2021 Impact Factor: 7.093
2020 SCImago Journal Rankings: 1.736

 

DC FieldValueLanguage
dc.contributor.authorLi, Wenliang-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorCetin, Kristen S.-
dc.contributor.authorYu, Sha-
dc.contributor.authorWang, Yu-
dc.contributor.authorLiang, Bingqing-
dc.date.accessioned2023-08-09T03:33:14Z-
dc.date.available2023-08-09T03:33:14Z-
dc.date.issued2018-
dc.identifier.citationBuilding and Environment, 2018, v. 136, p. 107-117-
dc.identifier.issn0360-1323-
dc.identifier.urihttp://hdl.handle.net/10722/329501-
dc.description.abstractUrban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa, U.S. First, 28 commercial and 6 residential building prototypes were designed by combining Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S. Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal patterns of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.-
dc.languageeng-
dc.relation.ispartofBuilding and Environment-
dc.subjectCalibration-
dc.subjectCityBEUM-
dc.subjectHigh spatiotemporal resolution-
dc.subjectUrban building energy use-
dc.titleDeveloping a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.buildenv.2018.03.036-
dc.identifier.scopuseid_2-s2.0-85044621008-
dc.identifier.volume136-
dc.identifier.spage107-
dc.identifier.epage117-

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