A Test Cell to Infer Thermal Response of Building Components for Model Predictive Control Using Building Automation Sensors

The use of Model Predictive Controllers (MPC) inbuilding HVAC systems has demonstrated significantenergy savings. This approach relies on knowledge ofoccupancy, weather conditions, and building thermaldynamics to predict the future HVAC conditioningrequirements. The thermal dynamics is usually modeledusing a grey box model, which requires the knowledgeof the buildings thermal mass, an unknown characteristicfor many older buildings. This study analyzes the abilityto determine thermal dynamic behavior without buildingconstruction knowledge. A test cell has been constructedto monitor typical building control points consisting ofthe ambient temperature, supply air conditions,occupancy, lighting, and plug loads along with outdoorair temperature and solar radiation. These are used inconjunction with surface temperature sensors tocharacterize their thermal response with the outdoor andindoor conditions. This paper presents the set-up of thetest cell along with the preliminary study investigatingthe ability to solve for thermal mass using sensormeasurements. The analysis conducted looks at thesimplest thermal condition of the cell, the nighttimeunoccupied condition, for the two most thermally slowelements, the concrete floor and ceiling slabs. Theresults from this preliminary analysis strongly indicatethe potential to calculate thermal dynamic behaviorusing only BAS points. This will support the overallresearch goal of creating model predictive controlapproaches for existing building where exact thermalmass is unknown.