Citation

Nateghi R, Guikema S, Quiring SM. Risk Anal. 2014; 34(6): 1069-1078.

Affiliation

Geography and Environmental Engineering, Johns Hopkins University, Baltimore, MD, USA.

Copyright

(Copyright © 2014, Society for Risk Analysis, Publisher John Wiley and Sons)

DOI

10.1111/risa.12131

PMID

24152061

Abstract

In this article, we discuss an outage-forecasting model that we have developed. This model uses very few input variables to estimate hurricane-induced outages prior to landfall with great predictive accuracy. We also show the results for a series of simpler models that use only publicly available data and can still estimate outages with reasonable accuracy. The intended users of these models are emergency response planners within power utilities and related government agencies. We developed our models based on the method of random forest, using data from a power distribution system serving two states in the Gulf Coast region of the United States. We also show that estimates of system reliability based on wind speed alone are not sufficient for adequately capturing the reliability of system components. We demonstrate that a multivariate approach can produce more accurate power outage predictions.

Language: en