The Thermal Network Approach to Model Occupants’ Heat and CO2 Generation Interactions: A Case Study in an Office Building in Panama

This investigation proposes a methodology to predict indoor air temperature and CO2 levels. For this, a two-occupant office inside a building in the Technological University of Panama is taken as a case study and modeled in Designbuilder simulation software validated via experimental data. Here, a mathematical model that considers internal heat gains by the occupants and CO2 emissions, including physical characteristics and activities developed, is constructed via the thermal network (RC) and system identification approaches. Three linear grey-box models are identified: a 4R2C for cooling system mode, a 3R2C for natural ventilation conditions, and a 1R1C for CO2 model. The results showed that the identified model is useful for estimating the indoor air temperature under both modes: “natural ventilation on” and “cooling system on,” in separated situations. Thus, it is determined that by incorporating the internal heat gain generated by the occupant in the model identification process, the data set is closer to real values than implementing a standard value as suggested by the literature. On the contrary, the CO2 model allowed an approximation between estimated and real data, but this prediction must be developed in a non-linear model for better results.