Fragmentation of outage clusters during the recovery of power distribution grids

Hao Wu, Xiangyi Meng, Michael M. Danziger, Sean P. Cornelius, Hui Tian () and Albert-László Barabási
Additional contact information
Hao Wu: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
Xiangyi Meng: Northeastern University
Michael M. Danziger: Northeastern University
Sean P. Cornelius: Ryerson University
Hui Tian: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
Albert-László Barabási: Northeastern University

Nature Communications, 2022, vol. 13, issue 1, 1-7

Abstract: Abstract The understanding of recovery processes in power distribution grids is limited by the lack of realistic outage data, especially large-scale blackout datasets. By analyzing data from three electrical companies across the United States, we find that the recovery duration of an outage is connected with the downtime of its nearby outages and blackout intensity (defined as the peak number of outages during a blackout), but is independent of the number of customers affected. We present a cluster-based recovery framework to analytically characterize the dependence between outages, and interpret the dominant role blackout intensity plays in recovery. The recovery of blackouts is not random and has a universal pattern that is independent of the disruption cause, the post-disaster network structure, and the detailed repair strategy. Our study reveals that suppressing blackout intensity is a promising way to speed up restoration.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-022-35104-9 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35104-9

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-35104-9

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().