  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.
