H.B. Keller Colloquium
Baosen Zhang received his Bachelor degree in Engineering Science from the University of Toronto and his PhD degree in Electrical Engineering and Computer Sciences from University of California, Berkeley. He was a Postdoctoral Scholar at Stanford University. He is currently an Associate Professor in the Department of Electrical and Computer Engineering at the University of Washington, Seattle, and holds the Keith and Nancy Endowed Professorship. His research interests are in control, optimization and AI for power and energy systems. He received the NSF CAREER award as well as several best paper awards.
Our electric grids are undergoing changes in both form and function, where renewable resources and new devices are creating systems that are more distributed, dynamic and uncertain. Modern AI and machine learning tools have the potential to transform the operation of these new energy systems. However, such algorithms typically do not provide guarantees about stability or safety, making them difficult to implement in practice. In this talk, I will describe how to bridge these gaps. I will show how structured neural networks can leverage advances in AI and provide formal guarantees such as system stability and hard constraint satisfaction. Then I will close the loop by discussing the challenge of supplying power to data centers and how it could be done efficiently and fairly, and how AI-based algorithms can be used in this respect.
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