The most frequent N-k line outages occur in motifs that can improve contingency selection

dc.contributor.author Zhou, Kai
dc.contributor.author Dobson, Ian
dc.contributor.author Wang, Zhaoyu
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2022-09-12T15:36:32Z
dc.date.available 2022-09-12T15:36:32Z
dc.date.issued 2022
dc.description.abstract Multiple line outages that occur together show a variety of spatial patterns in the power transmission network. Some of these spatial patterns form network contingency motifs, which we define as the patterns of multiple outages that occur much more frequently than multiple outages chosen randomly from the network. We show that choosing N-k contingencies from these commonly occurring contingency motifs accounts for most of the probability of multiple initiating line outages. This result is demonstrated using historical outage data for two transmission systems. It enables N-k contingency lists that are much more efficient in accounting for the likely multiple initiating outages than exhaustive listing or random selection. The N-k contingency lists constructed from motifs can improve risk estimation in cascading outage simulations and help to confirm utility contingency selection.
dc.description.comments This is a pre-print of the article Zhou, Kai, Ian Dobson, and Zhaoyu Wang. "The most frequent Nk line outages occur in motifs that can improve contingency selection." arXiv preprint arXiv:2209.02192 (2022). DOI: 10.48550/arXiv.2209.02192. Copyright 2022 The Authors. Posted with permission.
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/Dw88pZVw
dc.language.iso en
dc.publisher arXiv
dc.source.uri https://doi.org/10.48550/arXiv.2209.02192 *
dc.title The most frequent N-k line outages occur in motifs that can improve contingency selection
dc.type Preprint
dspace.entity.type Publication
relation.isAuthorOfPublication 16d1fad5-357e-4319-bb30-817987d0d818
relation.isAuthorOfPublication 06d3846d-d794-46b2-962a-c4d0569b2656
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff
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