Articles | Volume 45
Adv. Geosci., 45, 13–17, 2018
https://doi.org/10.5194/adgeo-45-13-2018
Adv. Geosci., 45, 13–17, 2018
https://doi.org/10.5194/adgeo-45-13-2018
 
19 Jul 2018
19 Jul 2018

Probabilistic short term wind power forecasts using deep neural networks with discrete target classes

Martin Felder et al.

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Latest update: 08 Aug 2022
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Short summary
In current applications of short term wind power forecasts, reliability information for the forecast is important because it helps decision making. Forecast errors are often estimated using ensembles of slightly disturbed weather predictions. Since this is very computation intensive, we propose a new method: A Deep Neural Network learns how reliable to forecast is, by comparing the current weather forecast with historical forecasts and the corresponding wind power production.