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Design matters: New...
Design matters: New insights on optimizing energy consumption for residential buildings
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- Sheng, Weili (författare)
- City University of Hong Kong
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- Kan, Xiaoming, 1988 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wen, Bo (författare)
- City University of Hong Kong
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- Zhang, Lin (författare)
- City University of Hong Kong
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(creator_code:org_t)
- Elsevier BV, 2021
- 2021
- Engelska.
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 242
- Relaterad länk:
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- In this paper, we construct a unique database for 1228 residential buildings in Hong Kong to investigate how the spatial features of these residential buildings affect the electricity consumption in the communal area. We choose Hong Kong for this analysis as the city owns a large number of standard-type residential buildings managed by the public institution, which could be affected strongly by environmental policies. Both the machine learning method, based on the Least Absolute Shrinkage and Selection Operator (LASSO), and econometric regressions are adopted to analyse the data. We first utilize the machine learning LASSO technique to identify the most relevant factors for the subsequent econometric analysis. Our results show that the electricity demand for relatively low consumption building types, such as Twin Tower, is 6% lower than that of the high consumption building types. Newly constructed buildings usually belong to the medium consumption types, with the estimated monthly electricity consumption per apartment in communal areas to be around 50.2 kWh on average in 2020. These findings shed light on the nexus between spatial features and energy use for complex buildings, potentially contributing to the better crafting of energy-saving policy and the improvement of residential building programmes.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Byggproduktion (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Construction Management (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Miljöanalys och bygginformationsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Environmental Analysis and Construction Information Technology (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Husbyggnad (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Building Technologies (hsv//eng)
Nyckelord
- Energy consumption
- Building type
- Machine learning
- LASSO method
- Building shape
- Spatial feature
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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