A major issue in future smart grid 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, producers etc. necessitates 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 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.
Na Li is an assistant professor in Electrical Engineering and Applied Mathematics of the School of Engineering and Applied Sciences in Harvard University since 2014. She received her PhD degree in Control and Dynamical systems from California Institute of Technology in 2013 and was a postdoctoral associate of the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology. Her research lies in the design, analysis, optimization and control of distributed network systems, with particular applications to power networks. She received NSF career award (2016) and entered the Best Student Paper Award ﬁnalist in the 2011 IEEE Conference on Decision and Control.