Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings

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 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.

Sustainable Building Design Development Knowledge Map: A Visual Analysis Using CiteSpace

“…H J H Brouwers, with P Spiesz and R Yu, focused on the impact resistance of the building material, Sustainable Ultra High Performance Fibre Concrete [19,20]. With Zhenjun Ma as the core and Georgios Kokogiannakis, Paul Cooper, Yi Guo, and Ali Aljubainawi as a collaborative group, Zhenjun Ma and Georgios Kokogiannakis proposed a model-based optimization of a ground source heat pump system design strategy that may also be applicable to design optimization strategies for other building energy systems [21]; Zhenjun Ma and Paul Cooper's research aimed primarily to create a stochastic model for determining the environmental and other driving conditions associated with the behaviour of residential buildings in relation to air conditioning use and the energy consumption of air conditioning operations [22]. Hongxing Yang, with Xi Chen, Gang Pei, Lin Lu, and Jinqing Peng, proposed the application of building information modelling (BIM) to the green building assessment scheme (GBA) [23] and a new passive design assessment system for a green building label [24].…”

New Approaches to Modelling Occupant Comfort

“…The fourth article continues the thread of modelling occupant behaviour. Jeong et al ( 2021) [8] developed a stochastic model of air conditioning usage based on field measurements in residential settings. Their dataset came from two years of measurements in 36 homes in Sydney, Australia.…”