Probabilistic intraday pv power forecast using ensembles of deep gaussian mixture density networks

HIGHLIGHTS

• who: Oliver Doelle and colleagues from the Siemens AG, Digital Industries-Data Visions, Siemenspromenade, Erlangen, Germany Faculty of Applied Computer Science, University of Augsburg, Augsburg, Germany have published the research work: Probabilistic Intraday PV Power Forecast Using Ensembles of Deep Gaussian Mixture Density Networks, in the Journal: Energies 2023, 646 of /2023/
• what: In industrial applications, however, the model structure and hyperparameters are rarely adapted over time or for different locations due to capacity reasons. For instance,, this approach had achieved better results than, e_g, a deep Gaussian process for load prediction. For a clear . . .
  

   

  

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