Evidence map›Paper›PMID 34306961›Full record

ArticleEnvironment systems & decisions2021

Critical Risk Indicators (CRIs) for the electric power grid: a survey and discussion of interconnected effects.

Judy P Che-Castaldo, Rémi Cousin, Stefani Daryanto, Grace Deng, Mei-Ling E Feng, Rajesh K Gupta, Dezhi Hong, Ryan M McGranaghan, Olukunle O Owolabi, Tianyi Qu and 9 more

Open access · bronzeAbstract read
In one paragraph

Article in Environment systems & decisions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 99% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 9 institutions in 3 countries.

Judy P Che-CastaldoConservation & Science Department, Lincoln Park Zoo, 2001 N. Clark St. Chicago, Chicago, IL USA.ORCID 0000-0002-9118-9202
Rémi CousinInternational Research Institute for Climate and Society, Earth Institute/Columbia University, New York, USA.
Stefani DaryantoDepartment of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, USA.
Grace DengDepartment of Statistics and Data Science, Cornell University, New York, USA.
Mei-Ling E FengConservation & Science Department, Lincoln Park Zoo, 2001 N. Clark St. Chicago, Chicago, IL USA.
Rajesh K GuptaHalicioglu Data Science Institute and Department of Computer Science & Engineering, University of California, San Diego, CA USA.
Dezhi HongHalicioglu Data Science Institute and Department of Computer Science & Engineering, University of California, San Diego, CA USA.
Ryan M McGranaghanAtmospheric and Space Technology Research Associates, Louisville, CO USA.
Olukunle O OwolabiDepartment of Civil and Environmental Engineering, Tufts University, Medford, MA USA.
Tianyi QuDepartment of Finance, Isenberg School of Management, UMASS Amherst, Amherst, MA USA.
Wei RenDepartment of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, USA.
Toryn L J SchaferDepartment of Statistics and Data Science, Cornell University, New York, USA.
Ashutosh SharmaCivil and Environmental Engineering, Pennsylvania State University, State College, PA USA.
Chaopeng ShenCivil and Environmental Engineering, Pennsylvania State University, State College, PA USA.
Mila Getmansky ShermanDepartment of Finance, Isenberg School of Management, UMASS Amherst, Amherst, MA USA.
Deborah A SunterDepartment of Civil and Environmental Engineering, Tufts University, Medford, MA USA.
Bo TaoDepartment of Plant and Soil Sciences, College of Agriculture, Food and Environment, University of Kentucky, Lexington, USA.
Lan WangDepartment of Management Science, Miami Herbert Business School, University of Miami, Coral Gables, FL USA.
David S MattesonDepartment of Statistics and Data Science, Cornell University, New York, USA.
Cornell University · USUniversity of Kentucky · USAmherst College · USHaliç University · TRLincoln Park Zoo · USPennsylvania State University · USTufts University · USAtmospheric and Space Technology Research Associates (United States) · USUniversity of Miami · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Critical risk indicatorElectric power gridMulti-disciplinaryRiskSystemic riskUncertainty

Identifiers

PMID34306961
PMCPMC8286170
OpenAlexW3122796019

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.