Volume 14: Low Carbon Cities and Urban Energy Systems: Part III

A Review of Data-driven Approaches for Occupant’s Behaviour in Building Energy Conservation Lin Zheng, Markus Mueller, Chunbo Luo, Xiaoyu Yan*

Abstract

Occupants behaviour (OB) has significant impacts on building energy performance and promoting sustainability. Imprecision of evaluating the impacts of the occupant behaviour brings about excess energy waste. On the other hand, the increased quantity and quality of the various building energy data collected promotes the use of data-driven approaches, while recognising the potential for building energy prediction as innovative choices. It is significant to conduct research on the data-driven methods for occupants’ behaviour in building energy management while considering the different impacts. In this regard, this paper aims to provide a literature review of the current research on data-driven methods for modelling, simulating and predicting the occupant’s behaviour and its impacts on building energy, highlighting the opportunities for further research in this context.

Keywords energy conservation in buildings, occupant’s behaviour, data-driven models, machine learning algorithm, sustainable building design