Articles | Volume 21, issue 2
https://doi.org/10.5194/nhess-21-607-2021
https://doi.org/10.5194/nhess-21-607-2021
Research article
 | 
11 Feb 2021
Research article |  | 11 Feb 2021

Predicting power outages caused by extratropical storms

Roope Tervo, Ilona Láng, Alexander Jung, and Antti Mäkelä

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Latest update: 24 Jun 2024
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Short summary
Predicting the number of power outages caused by extratropical storms is a key challenge for power grid operators. We introduce a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with a forest inventory. The storms are first identified from the data and then classified using several machine-learning methods. While there is plenty of room to improve, the results are already usable, with support vector classifier providing the best performance.
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