An IAQ and thermal comfort coach prototype to improve comfort and energy consumption thanks to adequate management of natural ventilation: development and first feedback results

Over time with thermal and energy regulations, buildings are increasingly insulated and airtight to control better the heat exchanges between the indoor and outdoor environments. The primary function of the mechanical ventilation system is to ensure healthy air by diluting odours and humidity with fresh air. However, in many situations, windows opening can be much more effective in terms of thermal comfort, air quality, or release heat loads due to a higher air change rate than the mechanical ventilation system itself. On the contrary, opening the windows can be counterproductive and, in particular, leads to overconsumption of energy because it is not necessarily obvious whether it is appropriate to open or close a window. In addition, opening a window can improve air quality and generate additional energy consumption, leading to a complex decision process.
This presentation presents a coaching tool developed to help occupants to know whether it is a good option to open or close their windows. The objective of this coach is to consider the three components: thermal comfort, indoor air quality (IAQ) and energy consumption. The coaching tool is based on environmental data monitored thanks to 3 sensors in its first version: indoor and outdoor air temperature and indoor CO2 concentration. The outside air temperature is first used to calculate the outdoor running temperature based on the last three days of measuring data. This running outdoor temperature is used to define the adaptive comfort temperature range. The indoor air temperature is then compared to both instantaneous outdoor air temperature and adaptive comfort temperature range to check if the thermal potential (heating or cooling) is in accordance with the thermal need of the indoor environment. In parallel, the IAQ is monitored thanks to the CO2 concentration sensors and compared to different ranges to define whether opening the window might be necessary to bring cleaner air into the room. All these data are integrated into a rule-based algorithm to determine the coaching advice, which might take three states: Open, Close or Free. The last one means open or close will neither improve nor deteriorate the indoor environment quality (IEQ). One of the challenges of this tool is to be autonomous in energy for at least one season. Energy consumption of the tool, frequency of computation of the algorithm and advice displayed to the user are other bottlenecks developed in parallel with the algorithm’s performance...