Power System Dynamics as Primal-Dual Algorithm for Optimal Load Control
Dec 02, 2013
from 01:00 PM to 02:30 PM
|Where||Engr. IV Bldg., Shannon Room 54-134|
|Contact Name||Prof. Jason Woo|
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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 (Caltech), Ufuk Topcu (UPenn), and Lina Li (MIT/Harvard)
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 boards of NOW Foundations and Trends in Networking and Foundations and Trends in Electrical Power Systems. He is an IEEE Fellow and received his B.S. from Cornell and PhD from Berkeley, both in EE.