In the Heat4Cool project, intelligent heating and cooling control system are explored, allowing the building to be monitored in real time through wireless sensor networks and energy meters, the creation and development of dynamic individual user profiles, weather forecast and structured data management. The goal is to achieve efficient energy supply and intelligent control of the HVAC and DHW systems.
In more detail, a standard BEMS framework is employed and enriched through a workflow which allows the estimation of end-user/occupant demand, which consists of the following steps: the learning and estimation of occupancy patterns, the identification of comfort conditions for the occupants via control actions on the level of the thermostat, combined with sensor measurements, and ultimately flexibility profiling, which enables further fine-tuning of the required baseline demand. The outcome of this process is a set of time-varying personalized setpoint limits, which are integrated in a Model Predictive Control (MPC) optimization framework.
A schematic of the workflow is given below.