Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings
Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/11/3/122 |
| _version_ | 1797540841001058304 |
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| author | Bongchan Jeong Jungsoo Kim Zhenjun Ma Paul Cooper Richard de Dear |
| author_facet | Bongchan Jeong Jungsoo Kim Zhenjun Ma Paul Cooper Richard de Dear |
| author_sort | Bongchan Jeong |
| collection | DOAJ |
| description | Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and actual energy use. The objective of this study was to develop a stochastic model for predicting occupant behaviour relating to A/C cooling and heating in residential buildings located in the Subtropical Sydney region of Australia. Multivariate logistic regression was used to estimate the probability of using A/C in living rooms and bedrooms, based on a range of physical environmental (outdoor and indoor) and contextual (season, day of week, and time of day) factors observed in 42 Sydney region houses across a two-year monitoring period. The resulting models can be implemented in building energy performance simulation (BEPS) tools to more accurately predict indoor environmental conditions and energy consumption attributable to A/C operation. |
| first_indexed | 2024-03-10T13:06:46Z |
| format | Article |
| id | doaj.art-657b0c4258fd4db081d09a9a887b9ce3 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-10T13:06:46Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-657b0c4258fd4db081d09a9a887b9ce32023-11-21T11:04:16ZengMDPI AGBuildings2075-53092021-03-0111312210.3390/buildings11030122Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential BuildingsBongchan Jeong0Jungsoo Kim1Zhenjun Ma2Paul Cooper3Richard de Dear4School of Architecture, Design and Planning, The University of Sydney, Sydney, NSW 2006, AustraliaSchool of Architecture, Design and Planning, The University of Sydney, Sydney, NSW 2006, AustraliaSustainable Buildings Research Centre (SBRC), University of Wollongong, Wollongong, NSW 2522, AustraliaSustainable Buildings Research Centre (SBRC), University of Wollongong, Wollongong, NSW 2522, AustraliaSchool of Architecture, Design and Planning, The University of Sydney, Sydney, NSW 2006, AustraliaAir conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and actual energy use. The objective of this study was to develop a stochastic model for predicting occupant behaviour relating to A/C cooling and heating in residential buildings located in the Subtropical Sydney region of Australia. Multivariate logistic regression was used to estimate the probability of using A/C in living rooms and bedrooms, based on a range of physical environmental (outdoor and indoor) and contextual (season, day of week, and time of day) factors observed in 42 Sydney region houses across a two-year monitoring period. The resulting models can be implemented in building energy performance simulation (BEPS) tools to more accurately predict indoor environmental conditions and energy consumption attributable to A/C operation.https://www.mdpi.com/2075-5309/11/3/122occupant behaviourair conditioningresidentialstochastic modellingbuilding energy performance simulation |
| spellingShingle | Bongchan Jeong Jungsoo Kim Zhenjun Ma Paul Cooper Richard de Dear Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings Buildings occupant behaviour air conditioning residential stochastic modelling building energy performance simulation |
| title | Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings |
| title_full | Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings |
| title_fullStr | Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings |
| title_full_unstemmed | Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings |
| title_short | Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings |
| title_sort | identification of environmental and contextual driving factors of air conditioning usage behaviour in the sydney residential buildings |
| topic | occupant behaviour air conditioning residential stochastic modelling building energy performance simulation |
| url | https://www.mdpi.com/2075-5309/11/3/122 |
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