A decision tool to balance indoor air quality and energy consumption: A case study

Abstract HVAC systems are responsible for a significant part of the total building energy consumption and in many cases a large portion of that energy is actually used inefficiently. The ability of these systems to adapt to changing numbers of occupants will play a major role in reducing their energy load. Demand Controlled Ventilation systems are helping towards that goal and many of them use CO 2 sensors as their core information source, whereby the system tries to maintain CO 2 near or under a specified set point. Besides providing a simple feedback mechanism, CO 2 can also be utilised in predictive models for indoor air quality and in the estimation of occupancy. The choice of location for the CO 2 sensors however can have an impact in the estimations. The objective of this study is two-pronged: Firstly to identify a relationship between occupancy, CO 2 setpoint, ventilation rate and cooling load for a university lecture theatre, in a way that it can be used as a decision tool by the facility manager to balance indoor air quality and energy consumption. Secondly, to investigate and quantify how representative the CO 2 values detected by different sensors within the lecture theatre are and whether any differences can have a significant effect in estimating the number of occupants within. Results show that both CO 2 and occupancy can be estimated with good accuracy with little effect from sensor placement and that it is feasible to easily visualise the balance between CO 2 threshold and cooling load for a given level of occupancy.