A Purdue research team led by Panagiota Karava, Jack and Kay Hockema Professor in Civil Engineering, has received a grant of nearly $1 million from the National Science Foundation to develop cyber-physical systems (CPS) aimed at reducing the energy consumption of buildings. The team also includes Jianghai  Hu, Professor of Electrical and Computer Engineering, and Ilias Bilionis, Associate Professor of Mechanical Engineering.

Collectively, buildings account for 40% of the US primary energy usage and CO2 emissions and 70% of the electricity consumption. Furthermore, buildings put a tremendous strain on the power grid as they are largely responsible for the peaks in energy demand. Making buildings smarter through the deployment of sensors, actuators, and controllers, which collectively serve as the backbone of building CPS, can achieve more than 30% annual energy savings and can also significantly smooth peak demand. Thus, smart buildings are vital to a sustainable energy future. However, the road to large-scale realization of smart buildings is inhibited by their heterogeneity, which requires engineering customized, site-specific, and, thereby, costly solutions.

The goal of this project is to develop a CPS solution for autonomous buildings that will enable non-expert building managers to deploy asset-specific, smart control policies. The advantage of the proposed solution relies on the fact that the approach can be applied on a large-scale even without any human intervention. The resulting software solution is the Artificial-Intelligence-Enabled Building Energy Expert (AI-BEE) and it will be demonstrated using simulations and experiments at the Center for High Performance Buildings at Purdue University. The proposed research will result in foundational contributions in core CPS areas, including machine learning and control, that will be translational to other application areas, such as large-scale energy systems (power grid), transportation, civil infrastructure, and unmanned vehicles.

More information on this project, including the full abstract, can be found on the NSF website.