An occupant behavior model based on artificial intelligence for energy building simulation

Occupants have influence on buildings performances due to their presence and their behavior towards in-door environmental conditions controls. However, most building energy models consider occupants in an over-simplified way. Many experiences feedbacks have shown that this assessment leads to huge dif-ferences between simulation results and actual energy consumption. In this paper we propose a new method aiming at reducing this uncertainty. It embeds mainly two models: a two-node thermophysiological model that calculates thermal sensation of a human being and an occupant behavior model based on artificial intelli-gence. Results of this new method are then presented and compared with actual data from field studies.