Approximately 84% of the life cycle energy use of a building is associated with operating the building. Building owners also face pressure to improve safety, security, occupant comfort and health, and to make buildings responsive to a new smart electrical grid that increasingly relies on the use of intermittent renewable energy sources. Modern integrated building automation and control systems create an environment rich with sensor data and distributed control intelligence that can be applied to solve these problems through the application of machine learning, intelligent optimization techniques, automated fault detections and diagnostics, automated commissioning tools, and management of local generation and flexible loads in response to changing electric grid conditions. The Intelligent Building Agents Laboratory is a unique, adaptable facility that can be used to test advanced control algorithms, generate data for modeling of equipment, test new ideas for grid responsiveness, etc.

References

     Pertzborn, A.J. (2022) ‘Implementation of Structured Reinforcement Learning for Supply Air Temperature Control’, presentation at 2022 ASHRAE Annual Conference, June 25-29, 2022, Toronto, ON.

     Pertzborn, A. J., Veronica, D.A. (2021) NIST Technical Note 2178: Baseline Control Systems in the Intelligent Building Agents Laboratory. doi: https://doi.org/10.6028/NIST.TN.2178.

key words

building control; intelligent agents; optimization; data analytics; machine learning; data-driven models

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants