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Identification of environmental and contextual driving factors of air conditioning usage behaviour in the sydney residential buildings

Journal Article


Abstract


  • Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants��� air conditioning usage patterns are often unrealisti-cally 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.

Publication Date


  • 2021

Citation


  • Jeong, B., Kim, J., Ma, Z., Cooper, P., & de Dear, R. (2021). Identification of environmental and contextual driving factors of air conditioning usage behaviour in the sydney residential buildings. Buildings, 11(3). doi:10.3390/buildings11030122

Scopus Eid


  • 2-s2.0-85103475895

Volume


  • 11

Issue


  • 3

Place Of Publication


Abstract


  • Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants��� air conditioning usage patterns are often unrealisti-cally 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.

Publication Date


  • 2021

Citation


  • Jeong, B., Kim, J., Ma, Z., Cooper, P., & de Dear, R. (2021). Identification of environmental and contextual driving factors of air conditioning usage behaviour in the sydney residential buildings. Buildings, 11(3). doi:10.3390/buildings11030122

Scopus Eid


  • 2-s2.0-85103475895

Volume


  • 11

Issue


  • 3

Place Of Publication