Abstract

Occupant behaviour plays a significant role in shaping the dynamics of energy consumption in buildings, but the complex nature of occupant behaviour has hindered a deeper understanding of its influence. A meta-analysis was conducted on 65 published studies that used data-driven quantitative assessments to assess energy-related occupant behaviour using the Knowledge Discovery and Data Mining (KDD) framework. Hierarchical clustering was utilised to categorise different modelling techniques based on the intended outcomes of the model and the types of parameters used in various models. This study will assist researchers in selecting the most appropriate parameters and methods under various data constraints and research questions. The research revealed two distinct model categories being used to study occupant behaviour-driven energy consumption, namely (i) occupancy status models and (ii) energy-related behaviour models. Multiple studies have identified limitations on data collection and privacy concerns as constraints of modelling occupant behaviour in residential buildings. The “regression model” and its variants were found to be the preferred model types for research that models “energy-related behaviour”, and “classification models” were found to be preferable for modelling “occupancy” status. There were only limited instances of data-driven studies that modelled occupant behaviour in low-income households, and there is a need to generate region-specific models to accurately model energy-related behaviour.

Highlights

  • Numerous studies have explored the behaviour of occupants within buildings and have drawn a direct connection between occupant behaviour and energy consumption.Most of these studies have focused on commercial building spaces

  • It is widely believed that occupant behaviour is one of the most difficult internal factors to model when it comes to predicting building energy consumption

  • Variations in occupant behaviour are the result of two variables: occupancy and behaviour

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Summary

Introduction

Numerous studies have explored the behaviour of occupants within buildings and have drawn a direct connection between occupant behaviour and energy consumption.Most of these studies have focused on commercial building spaces. Numerous studies have explored the behaviour of occupants within buildings and have drawn a direct connection between occupant behaviour and energy consumption. Quantitative assessments of occupant behaviour and its interaction with the building features, which influence energy conservation measures for lowincome households, are rare. Strategies can include adapting building design in response to the effects of a specific occupant behaviour or developing technical or design solutions that influence or modify specific human behaviour. Such approaches can be used to optimise energy consumption without compromising the indoor environmental quality and comfort of occupants. Variables that influence occupancy and occupant interaction with building features can be classified as (i) environment-related variables, (ii) time-related variables, or (iii) other random variables that explore the psychology of occupants [4]

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