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Article
Extracting resilience metrics from distribution utility data using outage and restore process statistics
arXiv
Document Type
Article
Disciplines
Publication Version
Submitted Manuscript
Publication Date
1-1-2020
Abstract
Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. Estimating the variability of restore duration allows us to predict a maximum restore duration with 95% confidence.
Copyright Owner
The Author(s)
Copyright Date
2020
Language
en
File Format
application/pdf
Citation Information
Nichelle'Le K. Carrington, Ian Dobson and Zhaoyu Wang. "Extracting resilience metrics from distribution utility data using outage and restore process statistics" arXiv (2020) Available at: http://works.bepress.com/ian-dobson/38/
This is a pre-print of the article Carrington, Nichelle'Le K., Ian Dobson, and Zhaoyu Wang. "Extracting resilience metrics from distribution utility data using outage and restore process statistics." arXiv preprint arXiv:2011.00693 (2020). Posted with permission.