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- Publisher Website: 10.1016/j.energy.2017.11.071
- Scopus: eid_2-s2.0-85037630426
- WOS: WOS:000423249200092
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Article: Modeling urban building energy use: A review of modeling approaches and procedures
Title | Modeling urban building energy use: A review of modeling approaches and procedures |
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Authors | |
Keywords | Bottom-up approaches Energy modeling Geospatial techniques Top-down approaches Urban building energy use |
Issue Date | 2017 |
Citation | Energy, 2017, v. 141, p. 2445-2457 How to Cite? |
Abstract | With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration. |
Persistent Identifier | http://hdl.handle.net/10722/329480 |
ISSN | 2023 Impact Factor: 9.0 2023 SCImago Journal Rankings: 2.110 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Wenliang | - |
dc.contributor.author | Zhou, Yuyu | - |
dc.contributor.author | Cetin, Kristen | - |
dc.contributor.author | Eom, Jiyong | - |
dc.contributor.author | Wang, Yu | - |
dc.contributor.author | Chen, Gang | - |
dc.contributor.author | Zhang, Xuesong | - |
dc.date.accessioned | 2023-08-09T03:33:05Z | - |
dc.date.available | 2023-08-09T03:33:05Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Energy, 2017, v. 141, p. 2445-2457 | - |
dc.identifier.issn | 0360-5442 | - |
dc.identifier.uri | http://hdl.handle.net/10722/329480 | - |
dc.description.abstract | With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration. | - |
dc.language | eng | - |
dc.relation.ispartof | Energy | - |
dc.subject | Bottom-up approaches | - |
dc.subject | Energy modeling | - |
dc.subject | Geospatial techniques | - |
dc.subject | Top-down approaches | - |
dc.subject | Urban building energy use | - |
dc.title | Modeling urban building energy use: A review of modeling approaches and procedures | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.energy.2017.11.071 | - |
dc.identifier.scopus | eid_2-s2.0-85037630426 | - |
dc.identifier.volume | 141 | - |
dc.identifier.spage | 2445 | - |
dc.identifier.epage | 2457 | - |
dc.identifier.isi | WOS:000423249200092 | - |