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

Viewed

Total article views: 3,480 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,656 770 54 3,480 59 50
  • HTML: 2,656
  • PDF: 770
  • XML: 54
  • Total: 3,480
  • BibTeX: 59
  • EndNote: 50
Views and downloads (calculated since 03 Aug 2020)
Cumulative views and downloads (calculated since 03 Aug 2020)

Viewed (geographical distribution)

Total article views: 3,480 (including HTML, PDF, and XML) Thereof 3,095 with geography defined and 385 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
Download
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.
Altmetrics
Final-revised paper
Preprint