An agent-based framework for studying occupant multi-comfort level in academic buildings -

Abstract

With the trend towards low energy or energy efficient buildings that diminish fossil fuel usage and carbon emissions, getting occupants actively involved during the design and operation phases of buildings is vital in achieving high energy performance without jeopardizing occupant satisfaction or comfort level. However, recent tools did not examine simultaneously, while considering different occupant behavior types, visual, thermal and acoustic comfort levels. This paper presents work targeted at efficiently studying occupant multi-comfort level using agent-based modeling with the ultimate aim of reducing energy consumption within academic buildings. The proposed model was capable of testing different parameters and variables affecting occupant behavior. Several scenarios were examined and statistical results demonstrated that (1) the presence of different occupant behavior types is deemed necessary for a more realistic overall model , (2) the absence of windows results in an acoustic satisfaction with an increase in HVAC off and medium level uses, and high lighting usage, and (3) the overall light usage decreases when two light switches instead of one are introduced.