TY - JOUR
T1 - Linking Cascading Failure Models and Organizational Networks to Manage Large-Scale Blackouts in South Korea
AU - Eisenberg, Daniel A.
AU - Park, Jeryang
AU - Seager, Thomas P.
N1 - Funding Information:
The authors would like to acknowledge Donghwan Kim for assistance with analysis, Younghan Chun for helping acquire South Korean power system data, and Taehun Lee for assisting with the translation of technical documents. Data for analysis were provided by the Korean Electric Power Corporation (KEPCO). This material is based upon work supported by the National Science Foundation (NSF) (Grant Nos. 1311230, 1441352, and 1415060). Daniel Eisenberg was supported by the US Defense Threat Reduction Agency (DTRA) under Grant DTRA-18681-M. Jeryang Park was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2016R1C1B1011770). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of KEPCO, the US federal government, or the South Korean federal government.
Publisher Copyright:
© 2020 American Society of Civil Engineers.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - Major blackouts are often attributed to cascading failures, where the failure of few power grid components causes large-scale loss of electricity. Despite recent innovations in modeling and predicting cascading losses, few studies link cascades to the complex management context of blackout response. This work broadens the purpose of cascading failure models to provide a heuristic method to study coordination plans to manage blackouts. The South Korean power grid is analyzed with a cascading failure model and the results are used to generate social networks of Korean organizations that respond to national blackouts. Organizations critical to cascading failure response are identified by analyzing resulting network models for power grids and social networks. The results of the study have key implications for Korea's blackout management policy because the organizations that constitute critical hubs for coordinating almost all cascading failures are small in number (e.g., betweenness ≥0.2). Also identified are highly connected organizations involved in a small number of cascading failures that may be able to provide backup support in case critical hubs are unavailable. Together, this work contributes methods to assess how emergency coordination can extend during cascades and demonstrates methods with an initial assessment for South Korea.
AB - Major blackouts are often attributed to cascading failures, where the failure of few power grid components causes large-scale loss of electricity. Despite recent innovations in modeling and predicting cascading losses, few studies link cascades to the complex management context of blackout response. This work broadens the purpose of cascading failure models to provide a heuristic method to study coordination plans to manage blackouts. The South Korean power grid is analyzed with a cascading failure model and the results are used to generate social networks of Korean organizations that respond to national blackouts. Organizations critical to cascading failure response are identified by analyzing resulting network models for power grids and social networks. The results of the study have key implications for Korea's blackout management policy because the organizations that constitute critical hubs for coordinating almost all cascading failures are small in number (e.g., betweenness ≥0.2). Also identified are highly connected organizations involved in a small number of cascading failures that may be able to provide backup support in case critical hubs are unavailable. Together, this work contributes methods to assess how emergency coordination can extend during cascades and demonstrates methods with an initial assessment for South Korea.
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U2 - 10.1061/(ASCE)ME.1943-5479.0000820
DO - 10.1061/(ASCE)ME.1943-5479.0000820
M3 - Article
AN - SCOPUS:85087639426
SN - 0742-597X
VL - 36
JO - Journal of Management in Engineering
JF - Journal of Management in Engineering
IS - 5
M1 - 4020067
ER -