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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/22978
Title: Critical Risk Indicators (CRIs) for the electric power grid: a survey and discussion of interconnected effects
Authors: Che-Castaldo J.P.
Cousin R.
Daryanto S.
Deng G.
Feng M.-L.E.
Gupta R.K.
Hong D.
McGranaghan R.M.
Owolabi O.O.
Qu T.
Ren W.
Schafer T.L.J.
Sharma, Ashutosh
Shen C.
Sherman M.G.
Sunter D.A.
Tao B.
Wang L.
Matteson D.S.
Published in: Environment Systems and Decisions
Abstract: The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human–natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in interconnected human–natural systems. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Citation: Environment Systems and Decisions, 41(4): 594-615
URI: https://doi.org/10.1007/s10669-021-09822-2
http://repository.iitr.ac.in/handle/123456789/22978
Issue Date: 2021
Publisher: Springer
Keywords: Critical risk indicator
Electric power grid
Multi-disciplinary
Risk
Systemic risk
Uncertainty
ISSN: 21945403
Author Scopus IDs: 55523615900
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55204679600
55229795900
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57222089377
57226167543
57204897094
57204024490
16680028200
57173625900
35109937400
57226161527
57224004581
54904485700
Author Affiliations: Che-Castaldo, J.P., Conservation & Science Department, Lincoln Park Zoo, 2001 N. Clark St. Chicago, Chicago, IL, United States
Cousin, R., International Research Institute for Climate and Society, Earth Institute/Columbia University, New York, United States
Daryanto, S., Department of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, United States
Deng, G., Department of Statistics and Data Science, Cornell University, New York, United States
Feng, M.-L.E., Conservation & Science Department, Lincoln Park Zoo, 2001 N. Clark St. Chicago, Chicago, IL, United States
Gupta, R.K., Halicioglu Data Science Institute and Department of Computer Science & Engineering, University of California, San Diego, CA, United States
Hong, D., Halicioglu Data Science Institute and Department of Computer Science & Engineering, University of California, San Diego, CA, United States
McGranaghan, R.M., Atmospheric and Space Technology Research Associates, Louisville, CO, United States
Owolabi, O.O., Department of Civil and Environmental Engineering, Tufts University, Medford, MA, United States
Qu, T., Department of Finance, Isenberg School of Management, UMASS Amherst, Amherst, MA, United States
Ren, W., Department of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, United States
Schafer, T.L.J., Department of Statistics and Data Science, Cornell University, New York, United States
Sharma, A., Civil and Environmental Engineering, Pennsylvania State University, State College, PA, United States, Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee, India
Shen, C., Civil and Environmental Engineering, Pennsylvania State University, State College, PA, United States
Sherman, M.G., Department of Finance, Isenberg School of Management, UMASS Amherst, Amherst, MA, United States
Sunter, D.A., Department of Civil and Environmental Engineering, Tufts University, Medford, MA, United States, Department of Mechanical Engineering, Tufts University, Medford, MA, United States, Tufts Institute of the Environment, Tufts University, Medford, MA, United States, Center for International Environment and Resource Policy at The Fletcher School, Tufts University, Medford, MA, United States
Tao, B., Department of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, United States
Wang, L., Department of Management Science, Miami Herbert Business School, University of Miami, Coral Gables, FL, United States
Matteson, D.S., Department of Statistics and Data Science, Cornell University, New York, United States
Funding Details: Funding was provided by the NSF Harnessing the Data Revolution (HDR) program, “Collaborative Research: Predictive Risk Investigation SysteM (PRISM) for Multi-layer Dynamic Interconnection Analysis” (Awards #1940160, 2023755, 1940176, 1940190, 1940208, 1940223, 1940276, 1940291, and 1940696). R. McGranaghan was partially supported under the NSF Convergence Accelerator Award to the Convergence Hub for the Exploration of Space Science (CHESS) team (NSF Award Number: 1937152). We would like to thank Suoan Gao (UMASS Amherst) for research assistance. Funding was provided by the NSF Harnessing the Data Revolution (HDR) program, ?Collaborative Research: Predictive Risk Investigation SysteM (PRISM) for Multi-layer Dynamic Interconnection Analysis? (Awards #1940160, 2023755, 1940176, 1940190, 1940208, 1940223, 1940276, 1940291, and 1940696). R. McGranaghan was partially supported under the NSF Convergence Accelerator Award to the Convergence Hub for the Exploration of Space Science (CHESS) team (NSF Award Number: 1937152). We would like to thank Suoan Gao (UMASS Amherst) for research assistance. 1937152; National Science Foundation, NSF: 1940160, 1940176, 1940190, 1940208, 1940223, 1940276, 1940291, 1940696, 2023755
Corresponding Author: Che-Castaldo, J.P.; Conservation & Science Department, 2001 N. Clark St. Chicago, United States; email: jchecastaldo@lpzoo.org
Appears in Collections:Journal Publications [HY]

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