Probabilistic behavioural modeling in building performance simulation—The Brescia eLUX lab

摘要: Abstract Occupant’s behavioural patterns determine a significant level of uncertainty in building energy performance evaluation. It is difficult to account for this the design phase when operational and occupancy profiles are unknown. The relevant “performance gap” usually encountered between simulated measured clearly connected biased assumptions modeling, especially initial phase. A probabilistic modeling approach proposed improve simulation reliability robustness with respect variability patterns. case study presented eLUX lab “Smart Campus” Brescia University Italy. Occupancy dependent input parameters such as air change rates (i.e. mechanically controlled ventilation) internal heat gains due people, lighting appliances) described by means probability distributions obtain thermal demand load output. Probabilistic results enables more reliable identification saving strategies (operational environmental settings) highly variable operating conditions. Further, data processed weather-adjusted visualization, suitable establishing continuity operation phases, calibration purpose. Calibrated models can be used several specific tasks phase, particular condition monitoring, fault detection diagnosis, supervisory control management. For presented, detailed acquisition scheme has been designed enable an effective monitoring activity aimed at experimenting model-based approaches reported. research point-of-departure general assessing critically issues obtained conventional approaches, occupants’ behaviour, exploiting same time possibility using direct feedback promote change.