Dr. Sahra Sedigh is an Associate Professor of Electrical and Computer Engineering and Computer Science (courtesy) and a Research Investigator with the Intelligent Systems Center at the Missouri University of Science and Technology. She holds a BS in electrical engineering from the Sharif University of Technology, and an MS in electrical engineering and PhD in electrical and computer engineering from Purdue University. Her current research centers on development and modeling of dependable networks and systems, with focus on critical infrastructure. Her projects include research on dependability of the electric power grid, large-scale water distribution networks, and transportation infrastructures. Her industry experience includes research and development of high availability mechanisms for the Cisco Internetwork Operating System. Her past and present research sponsors include the National Science Foundation, the US and Missouri Departments of Transportation, the Department of Education, the National Security Agency, the Army, the EU FP7 Program on Smart Monitoring of Historic Structures, and private industry. She is a Fellow of the National Academy of Engineering’s Frontiers of Engineering Education Program and held a Purdue Research Foundation Fellowship from 1996 to 2000. She is a Senior Member of the IEEE and a member of IEEE-HKN.
S. Sedigh Sarvestani (email@example.com), K. Marashi, and A. R. Hurson
Dept. of Education; Dept. of Transportation; Intelligent Systems Center (Missouri S&T); Center for Infrastructure Engineering Studies (Missouri S&T); IntelliSpeak, LLC
This research seeks to facilitate analysis of the reliability and survivability achieved by smart grids. To this end, we have proposed an analytical reliability model and a survivability analysis method that capture the effect of impairments originating from both physical and cyber components, as well as the effect of cyber-physical interdependencies among these components. We investigate the use of simulation-based fault injection to instantiate the model with failure data. We aim to categorize and quantify dependencies in the smart grid and analyze the impact on reliability of introducing additional interdependencies. A pending case study investigates the effect of physical and cyber improvements on overall reliability of the smart grid, and demonstrates that flawed cyber infrastructure can result in lower reliability than that of a conventional power grid with less advanced control. Additional detail on the project is available here.