IN022-01
Critical Risk Indicators (CRIs) for the electric power grid: A survey and discussion of interconnected effects

Thursday, 10 December 2020: 19:00
Virtual
Rajesh Gupta, University of California San Diego, HDSI and CSE, La Jolla, CA, United States, Mila Sherman, University of Massachusetts Amherst, Amherst, MA, United States, Dezhi Hong, University of California San Diego, La Jolla, CA, United States, Judy P Che-Castaldo, Lincoln Park Zoo, Chicago, United States, Ryan Michael McGranaghan, Atmospheric and Space Technology Research Associates (ASTRA), Louisville, CO, United States, Deborah A Sunter, Tufts University, Medford, United States, Chaopeng Shen, Pennsylvania State University Main Campus, Department of Civil and Environmental Engineering, University Park, PA, United States, Rémi Cousin, Columbia University, International Research Institute for Climate and Society, Palisades, NY, United States, David Matteson, Cornell University, Ithaca, NY, United States, Lan Wang, University of Minnesota, Minneapolis, United States and Wei Ren, University of Kentucky, Lexington, KY, United States
Abstract:
Human-natural systems, like the electric power grid, are the complex culmination of interdependent processes. These interdependencies between diverse components in a system can provide profound insights on the health and risk states of the system as a whole, yet there is a dearth of rigorous definition, understanding, and synopsis of indicators of risk for society's most important systems. In this paper, we conduct a survey of risk indicators for the electric power grid, identifying those indicators across a range of domains that must be considered to improve the resiliency of the power grid. We survey and provide methodologies for critical risk indicators in energy, finance, climate, ecology, space weather, hydrology, and agriculture domains. We culminate the survey with a discussion about converging indicators from individual domains to explore systemic risk, i.e., risk arising from interconnection of human-natural systems.
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