Fragmentation of outage clusters during the recovery of power distribution grids

Hao Wu, Xiangyi Meng, Michael M. Danziger, Sean P. Cornelius, Hui Tian*, Albert László Barabási

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

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.

Original languageEnglish
Article number7372
JournalNature Communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022
Externally publishedYes

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