Detailed occupancy prediction, occupancy-sensing control and advanced behavioural modelling within whole-building energy simulation

TLDR: Results suggest that for both heating and coolingdominant climates, adaptive comfort control effectively reduces cooling requirements, yet operable window use during cooler conditions appear to increase heating requirements.

Abstract: This study sets out to bridge the gap between building energy simulation and empirical evidence on occupant behaviour. The major output is a self-contained simulation module that aims to control all occupant-related phenomena which can affect energy use in buildings. It provides high resolution and high frequency occupancy prediction (i.e. when occupants as individual agents occupy a modelled environment), occupant-sensing control (i.e. as driven by the mere presence of one or more occupants, such as occupancy-sensing lighting controls), as well as advanced behavioural models (i.e. active personal control, such as manual switching of lights, manual adjustments to window blinds, operable windows, personalized air-conditioning units). The module is integrated within the ESP-r free software, a whole-building energy simulation program. Simulation results clearly show that occupants-based phenomena exert a strong influence on simulated energy use, revealing a number of limitations in key assumptions in current energy simulation practice. Key behavioural traits, commonly associated to lighting behavioural patterns, also appear to be associated to personal control of operable windows, as demonstrated in a pilot field study in a Université Laval pavilion in Québec. This may suggest an abstract quality to certain behavioural concepts regarding different environmental controls. The study then focuses on the use of the developed work to investigate the energy saving potential of novel yet untried strategies: adaptive comfort control algorithms in hybrid environments, based on the use of operable windows as switching mechanisms between natural and artificial modes of environmental control. Results suggest that for both heatingand coolingdominant climates, adaptive comfort control effectively reduces cooling requirements, yet operable window use during cooler conditions appear to increase heating requirements. The usefulness of the original method is here illustrated by providing a more complete view on energy use attributed to occupant behaviour. 2 http://www.gnu.org/