Junbo Zhao, an assistant professor at the University of Connecticut’s Department of Electrical and Computer Engineering and the grid modernization team lead at Eversource Energy Center, has received a grant for his work in advanced microgrid optimization and control.
This is a collaborative proposal with National Renewable Energy Lab entitled “Physics-Informed Intelligent and Proactive Building Load Management for Energy Resilience” in response to DoD ESTCP’s FY2022 FOA. This project proposes to encode load flexibility harnessing technologies with novel physics-informed multi-agent deep reinforcement learning (MADRL) proactive control algorithms for advanced load management. The load flexibility harnessing allows improving energy efficiency under normal operation as well as providing helpful load information for emergent energy control during grid outages. MADRL enables us to embed the dynamic impacts of load shedding into the online optimal control of energy resources and loads during grid outages. More information about the ESTCP and the selected projects can be found here.
Zhao’s research interests include cyber-physical power system modeling, monitoring, uncertainty quantification, learning, dynamics, stability control, and cyber security with distributed energy resources. More information about him and his research can be found here.
Published: February 9, 2022
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