Using Utility Outage Statistics to Quantify Improvements in Bulk Power System Resilience
| dc.contributor.author | Kelly-Gorham, Molly Rose | |
| dc.contributor.author | Hines, Paul D.H. | |
| dc.contributor.author | Zhou, Kai | |
| dc.contributor.author | Dobson, Ian | |
| dc.contributor.department | Department of Electrical and Computer Engineering | |
| dc.date.accessioned | 2024-11-13T17:17:15Z | |
| dc.date.available | 2024-11-13T17:17:15Z | |
| dc.date.issued | 2020-08-13 | |
| dc.description.abstract | CRISP is a new high-level statistical approach driven by utility data to quantify resilience in electric power transmission networks. We extend CRISP to model energy storage, photovoltaics, and generator outages, to account for the spatial spread of cascading outages, and to optimize the restoration process. Illustrative results show how CRISP can measure the resilience impact of combinations of energy storage and photovoltaics on a power system. | |
| dc.description.comments | This is a manuscript of the article published as Kelly-Gorham, Molly Rose, Paul DH Hines, Kai Zhou, and Ian Dobson. "Using utility outage statistics to quantify improvements in bulk power system resilience." Electric Power Systems Research 189 (2020): 106676. doi: https://doi.org/10.1016/j.epsr.2020.106676. | |
| dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/aw4NM93r | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.rights | This manuscript is made available under the Elsevier user license (https://www.elsevier.com/open-access/userlicense/1.0/). | |
| dc.source.uri | https://doi.org/10.1016/j.epsr.2020.106676 | * |
| dc.subject.disciplines | DegreeDisciplines::Engineering::Electrical and Computer Engineering::Power and Energy | |
| dc.subject.disciplines | DegreeDisciplines::Physical Sciences and Mathematics::Statistics and Probability::Statistical Models | |
| dc.subject.disciplines | DegreeDisciplines::Engineering::Electrical and Computer Engineering | |
| dc.subject.keywords | Cascading outages | |
| dc.subject.keywords | Energy storage | |
| dc.subject.keywords | Resilience | |
| dc.subject.keywords | Restoration | |
| dc.subject.keywords | Statistical modeling | |
| dc.subject.keywords | Transmission system | |
| dc.title | Using Utility Outage Statistics to Quantify Improvements in Bulk Power System Resilience | |
| dc.type | article | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 16d1fad5-357e-4319-bb30-817987d0d818 | |
| relation.isOrgUnitOfPublication | a75a044c-d11e-44cd-af4f-dab1d83339ff |
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