Prof. Venu Veeravalli
Title: Quickest Detection and Isolation of Line Outages in Power Systems
Abstract: The problem of detecting abrupt changes in stochastic systems and time series, often referred to as the quickest change detection (QCD) problem, arises in various branches of science and engineering. It is assumed that the observations undergo achange in distribution in response to a change or disruption in the environment or, more generally, to changes in certain patterns. The observations are obtained sequentially and, as long as their behavior is consistent with the normal state, the process is allowed to continue. If the state changes, then it is of interest to detect the change as soon as possible, subject to false alarm constraints, and take any necessary action in response to the change. In the first part of this talk, an up-to-date overview of the results on the QCD problem will be provided, including some recent results on data-efficient QCD. A number of applications of QCD will be discussed. In the second part of the talk, the focus will be on the problem of detecting and isolating line outages in power systems using phasor measurement unit (PMU) measurements taken at the buses. It is shown that QCD based algorithms are tailor-made for this problem and significantly outperform existing methods.
Biography: Dr. Veeravalli, received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1992, the M.S. degree from Carnegie-Mellon University in 1987, and the B.Techdegree from Indian Institute of Technology, Bombay (Silver Medal Honors) in 1985. He is currently a Professor in the department of Electrical and Computer Engineering (ECE), the Coordinated Science Laboratory (CSL) and the Information Trust Institute (ITI) at the University of Illinois at Urbana-Champaign. He was on the faculty of the School of ECE at Cornell University before he joined Illinois in 2000. He served as a program director for communications research at the U.S. National Science Foundation in Arlington, VA during 2003-2005. His research interests span the theoretical areas of detection and estimation, information theory, statistical learning, and stochastic control, with applications to wireless communication systems and networks, sensor networks, cyberphysicalsystems, big data, and genomics. He is a Fellow of the IEEE, and a recipient of the 1996 IEEE Browder J. Thompson Best Paper Award and the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE). He served as a distinguished lecturer for the IEEE Signal Processing Society during 2010-2011.