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University of Cambridge > Talks.cam > Signal Processing and Communications Lab Seminars > Estimation with Incomplete State Information in the Smart Grid
Estimation with Incomplete State Information in the Smart GridAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Prof. Ramji Venkataramanan. Abstract: The increasing interconnectivity between information systems, communications, and the electricity grid gives rise to the smart grid. A characteristic that draws a distinction between the current grid and the smart grid is the availability of information that can be used to optimize the system management. This implies that additional networks of sensing and communication need to be added to the grid, which amplifies the impact of potential threats, both intentional and unintentional. In this talk we analyze the network state estimation problem with incomplete state information. A common approach is to assume that the underlying random process modeling the network state is stationary and its statistical characterization is known. Unfortunately, this is not a realistic assumption. That being the case, the imperfect knowledge of the statistical model needs to be taken into account when analyzing the fundamental limits governing the system and in the design of practical estimation procedures. First we study the theoretical limits for grid state estimation when partial prior knowledge is available using information theoretic measures and random matrix theory. We show that the uncertainty about the system model can be absorbed as a mismatch term defined by a random process. This framework enables us to describe the trade-offs between the estimation performance and the amount of prior knowledge available during the estimation process. In a second part, we design practical estimation/attack strategies when data injection attacks are present. The validity of the presented procedures in real settings is studied through simulations in the IEEE test systems. Bio: Iñaki Esnaola received the M.S. degree in Electrical Engineering from University of Navarra, Donostia, Spain in 2006 and a Ph.D. in Electrical Engineering from University of Delaware, Newark, DE in 2011. He is currently a Postdoctoral Research Associate at Princeton University, Princeton, NJ. In 2010-2011 he was a Research Intern with Bell Laboratories, Alcatel-Lucent, Holmdel, NJ. His research interests include information theory and communication theory. This talk is part of the Signal Processing and Communications Lab Seminars series. This talk is included in these lists:
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