Robust occupancy-based distributed demand control ventilation

Distributed demand control ventilation (DDCV) has shown potential for improving both indoor air quality (IAQ) and energy consumption over conventional ventilation systems. However, ventilation strategies based on measurements of CO₂ concentrations suffer from several shortcomings due to issues related to accuracy and drift of off-the-shelf CO₂ sensors as well as the highly non-uniform distribution of CO₂ in typical office environments. In this paper, an alternative approach for DDCV is considered in which ventilation air and its conditions are modulated based on definitive knowledge of occupancy in a zone. Using energy and contaminant simulations, it is shown that it is possible to improve both energy consumption and IAQ by following this approach. Furthermore, the effects of uncertainties in occupancy estimates on IAQ and energy consumption are analysed to demonstrate the robustness of the proposed DDCV systems. Finally, some discussion on practical implementation of occupancy-based DDCV systems including occupancy sensors is provided.