EECS Seminar: Distributed Energy Management with Limited Communication

Abstract: A major issue in future power grids is how intelligent devices and independent producers can respectively change their power consumption/production to achieve near maximum efficiency for the power network. Limited communications between devices and producers necessitate an approach where the elements of the network can act in an autonomous manner with limited information/communications, yet achieve near-optimal performance. In this talk, I will present our recent work on distributed energy management with limited communication. In particular, I will show how we can extract information from physical measurements and recover information from local computation. We will also investigate the minimum amount of communication for achieving the optimal energy management and study how limited communication affects the convergence rate of the distributed algorithms. We will conclude the talk with a discussion on challenges and opportunities on distributed optimization and control for future grids.

Bio: Na Li has been an assistant professor in electrical engineering and applied mathematics at Harvard University's School of Engineering and Applied Sciences since 2014. She received her bachelor's degree in mathematics from Zhejiang University in 2007 and a doctorate in control and dynamical systems from California Institute of Technology in 2013. She was a postdoctoral associate of the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology 2013-2014. Her research lies in the design, analysis, optimization and control of distributed network systems with particular applications to power networks. She received an NSF career award (2016) and was a Best Student Paper Award finalist in the 2011 IEEE Conference on Decision and Control.