Abstract

Renewable energy integration and resilience to disasters motivate the need for flexible resources in electric power systems. Distributed energy resources (DERs), such as electric vehicles and thermostatically controlled loads, represent an intriguing set of distributed assets to provide flexible services in power systems. This talk addresses modeling, estimation, and control for aggregations of DERs. Specifically, the talk is divided into two parts. First, we discuss a partial differential equation (PDE) approach to modeling and estimating aggregations of DERs. Second, we discuss a novel class of methods for controlling DER populations that are mathematically formulated as large-scale mixed integer programs. We call this class of methods "Hopfield Methods."

Bio

Scott Moura is an Assistant Professor at the University of California, Berkeley in Civil & Environmental Engineering and Director of eCAL. He received the Ph.D. degree from the University of Michigan in 2011, the

M.S. degree from the University of Michigan in 2008, and the B.S. degree from the UC Berkeley, in 2006 - all in Mechanical Engineering. He was a postdoctoral scholar at UC San Diego in the Cymer Center for Control

Systems and Dynamics, and a visiting researcher in the Centre Automatique et Systèmes at MINES ParisTech in Paris, France. He is a recipient of the O. Hugo Shuck Best Paper Award, Carol D. Soc Distinguished Graduate Student Mentoring Award, Hellman Faculty Fellows Award, UC Presidential Postdoctoral Fellowship, National Science Foundation Graduate Research Fellowship, University of Michigan Distinguished ProQuest Dissertation Honorable Mention, University of Michigan Rackham Merit Fellowship, and Distinguished

Leadership Award. His research interests include control & estimation theory for PDEs, optimization, machine learning, batteries, electric vehicles, and the distributed energy resources.