Safe and Efficient Operation of Energy Systems Through Structured Learning

Baosen Zhang (University of Washington)

Feb 15, 2023
10:00 am to 11:00 am | Science and Engineering Complex (SEC), LL2.224 | Remote option

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 on stability or safety, making them difficult to implement in practice. In this talk, I will describe how to bridge the gap between learning and the need to satisfy safety-critical constraints. Through applications in building energy management, frequency control, and optimal power flow problems, I will show how structured neural networks can leverage advances in machine learning and provide formal guarantees such as system stability and hard constraint satisfaction.

Speaker Bio

Baosen Zhang is the Keith and Nancy Endowed Career Development Professor in Electrical and Computer Engineering at the University of Washington. He received a Bachelor degree from the University of Toronto, a PhD degree from University of California, Berkeley, and he was a postdoc at Stanford University. Baosen's research interests are in the power and energy systems, using tools from control, optimization and learning to improve the sustainability, efficiency and reliability of the electric grid. He received the NSF CAREER award as well as several best paper awards.


Douglas Woodhouse