We formulate an optimal load control (OLC) problem in power networks where the objective is to minimize the aggregate cost of tracking an operating point subject to power balance over the network. We prove that the swing dynamics and the branch power flows, coupled with frequency-based load control, serve as a distributed primal-dual algorithm to solve OLC. Even though the system has multiple equilibrium points, we prove that it nonetheless converges to an optimal point. This result implies that the local frequency deviations at each bus convey exactly the right information about the global power imbalance for the loads to make individual decisions that turn out to be globally optimal. It allows a completely decentralized solution without explicit communication among the buses. Simulations show that the proposed OLC mechanism can resynchronize bus frequencies with significantly improved transient performance.

Joint work with Changhong Zhao, Ufuk Topcu, and Na Li. (Zhao and Low are with Caltech; Li is with MIT/Harvard; Topcu is with UPenn.)

Steven H. Low is a Professor of the Computing & Mathematical Sciences and Electrical Engineering Departments at Caltech. Before that, he was with AT&T Bell Laboratories, Murray Hill, NJ, and the University of Melbourne, Australia. He was a co-recipient of IEEE best paper awards, the R&D 100 Award, and an Okawa Foundation Research Grant. He is a Senior Editor of the IEEE Journal on Selected Areas in Communications, a Senior Editor of the IEEE Trans. Control of Network Systems, a Steering Committee Member of the IEEE Trans. Network Science & Engineering, and on the editorial board of NOW Foundations and Trends in Networking. He is an IEEE Fellow and received his B.S. from Cornell and PhD from Berkeley, both in EE.

A defining feature of a smart grid is its ability to adapt to changing operating conditions and contingencies by leveraging advanced sensing, communication, and networking capabilities. However, relying networking for grid monitoring and real time operation comes with increasing security risks of cyber-attacks.

In this talk, we consider man-in-the-middle attacks on the power grid where an adversary manipulates analog and digital data with the goal of misleading the control center with an incorrect network topology and operating state. Two types of attacks are considered. The first type of attacks avoid detection by the control center and covertly change the system operating state. The second type of attacks openly attack the control center but hide the actual source of attack. We discuss the impacts of man-in-the-middle attacks on market operations and possible counter measures of such attacks.

Lang Tong is the Irwin and Joan Jacobs Professor in Engineering at Cornell University and the Cornell site director of the Power Systems Engineering Research Center (PSERC). He received the B.E. degree from Tsinghua University, Beijing, China, and PhD degree in EE from the University of Notre Dame, Notre Dame. He was a Postdoctoral Research Affiliate at the Information Systems Laboratory, Stanford University. Lang’s research interests lie in the general areas of statistical inference, decisions, communications, and complex networks. His current research focuses on energy and power systems and related data analytics. He received the 2004 Best Paper Award from the IEEE Signal Processing Society, the 2004 Leonard G. Abraham Prize Paper Award from the IEEE Communications Society, and the 1993 Outstanding Young Author Award from the IEEE Circuits and Systems Society. He is also a coauthor of seven student paper awards. He is a Fellow of IEEE.

Ram Rajagopal is an Assistant Professor of Civil and Environmental Engineering at Stanford University, where he directs the Stanford Sustainable Systems Lab (S3L), focused on large scale monitoring, data analytics and stochastic control for infrastructure networks, in particular energy and transportation. His current research interests in power systems are in integration of renewables, smart distribution systems and demand-side data analytics. Prior to his current position he was a DSP Research Engineer at National Instruments and a Visiting Research Scientist at IBM Research. He holds a Ph.D. in Electrical Engineering and Computer Sciences and an M.A. in Statistics, both from the University of California Berkeley, Masters in Electrical and Computer Engineering from University of Texas, Austin and Bachelors in Electrical Engineering from the Federal University of Rio de Janeiro. He is a recipient of the Powell Foundation Fellowship, Berkeley Regents Fellowship and the Makhoul Conjecture Challenge award. He holds more than 30 patents from his work, and has advised or founded various companies in the fields of sensor networks, power systems and data analytics.