Bayesian estimates of transmission line outage rates that consider line dependencies

Date
2020-01-01
Authors
Zhou, Kai
Cruise, James
Dobson, Ian
Dent, Chris
Dobson, Ian
Wehenkel, Louis
Wang, Zhaoyu
Wilson, Amy
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Dobson, Ian
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Abstract

Transmission line outage rates are fundamental to power system reliability analysis. Line outages are infrequent, occurring only about once a year, so outage data are limited. We propose a Bayesian hierarchical model that leverages line dependencies to better estimate outage rates of individual transmission lines from limited outage data. The Bayesian estimates have a lower standard deviation than estimating the outage rates simply by dividing the number of outages by the number of years of data, especially when the number of outages is small. The Bayesian model produces more accurate individual line outage rates, as well as estimates of the uncertainty of these rates. Better estimates of line outage rates can improve system risk assessment, outage prediction, and maintenance scheduling.

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<p>This is a pre-print of the article Zhou, Kai, James R. Cruise, Chris J. Dent, Ian Dobson, Louis Wehenkel, Zhaoyu Wang, and Amy L. Wilson. "Bayesian estimates of transmission line outage rates that consider line dependencies." <em>arXiv preprint arXiv:2001.08681</em> (2020). Posted with permission.</p>
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