A cornerstone of the smart grid is to advance the monitoring of its assets and operations. Increasing installation of the phasor measurement units (PMUs) benefits the power system monitoring with the fast and synchronized data to capture the grid dynamics. In this talk, I will first introduce the exciting idea of using sparse signal recovery for efficient identifying power line outages from PMU data. The proposed methods, at only linear computational complexity, exhibit competitive performance to the benchmark exhaustive-search method. The second part will focus on how to deploy PMU devices for improving the performance of identifying line outages. The vision here is to equip power system operators with tools to quickly diagnose and thus effectively respond to faults and instabilities.
Hao Zhu is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign (UIUC), teaching in Power and Energy Systems. She received the B.E. degree from Tsinghua University, China, in 2006, and the M.Sc. and Ph.D. degrees from the University of Minnesota (UMN), Twin Cities, in 2009 and 2012, all in electrical engineering. After that, she worked as a Postdoctoral Research Associate at the Information Trust Institute, UIUC. Her current research interests include power system operations and control, smart grid, and (distributed) statistical signal processing.