Capturing Thermal Dynamics in Air-Conditioned Rooms

Thermostatically controlled loads (TCLs) play a crucial role in reducing energy consumption in buildings. Thus, developing accurate models that enable the effective implementation of energy control strategies is essential. With this goal in mind, a model of a room influenced by an air conditioning (AC) unit was developed as an initial starting point for our research into TCL systems modeling and control. In this work, a data-driven modeling approach was utilized, employing data collected from an ad-hoc data collection platform. In addition, an algorithm was developed to determine the AC’s operational states. The results, based on RMSE (Root Mean Square Error) and MAXAE (Maximum Absolute Error) metrics, demonstrate the effectiveness of the proposed algorithm and data-driven modeling approach in capturing the thermal dynamics of the room under the influence of the AC unit.