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Optimal Building Controls: from Sensor Placement to Control Implementation
14 Mar 2014 09:00
In the United States, the buildings sector accounts for nearly 41 percent of the primary energy consumption, in which a significant amount is consumed by their heating, ventilation, and air-conditioning (HVAC) systems. Optimal building controls, such as model predictive control (MPC), could help improve the energy efficiency of HVAC systems and therefore reduce the overall energy consumption in buildings. MPC is particularly attractive because of its significant potential for energy savings (or energy cost savings) and its many advantages. This talk discusses our research on the end-to-end process of developing MPC for a building's HVAC system, from sensor placement to building model training, advanced building controls simulation, and MPC implementation. We show how the quality of sensor data, which is influenced by sensor placement, could affect the inverse model's accuracy and eventually the control performance. This talk is based on our research project in the Energy Efficient Buildings Hub (EEB Hub), established by the U.S. Department of Energy in Philadelphia.
- Place
- T2:C4-78
- Organizer
- UCEEB
- Contact person
- Karolína Tomešová, karolina.tomesova@uceeb.cvut.cz