Mixture Density Networks per hour-month applied to wind power generation forecast

Damian Vallejo,Ruben Chaer

doi:10.1109/urucon53396.2021.9647384

Mixture Density Networks per hour-month applied to wind power generation forecast

Damian Vallejo, Ruben Chaer

https://doi.org/10.1109/urucon53396.2021.9647384

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Publication Date: Nov 24, 2021

#Set Of Networks #Mixture Density Networks + Show 8 more

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Abstract

In this work, the training of a set of Mixture Density Networks (MDNs) type of Neural Networks (NNs) is presented. This set of networks is used to forecast the power generated by a wind farm in Uruguay. The advantages and challenges of using a MDN per hour-month against a single MDN are discussed.

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