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@INPROCEEDINGS{Trebbien:1025665,
      author       = {Trebbien, Julius and Pütz, Sebastian and Schäfer,
                      Benjamin and Nygård, Heidi S. and Gorjão, Leonardo Rydin
                      and Witthaut, Dirk},
      title        = {{P}robabilistic {F}orecasting of {D}ay-{A}head
                      {E}lectricity {P}rices and their {V}olatility with {LSTM}s},
      publisher    = {IEEE},
      reportid     = {FZJ-2024-03054},
      pages        = {1},
      year         = {2023},
      comment      = {2023 IEEE PES Innovative Smart Grid Technologies Europe
                      (ISGT EUROPE) : [Proceedings] - IEEE, 2023. - ISBN
                      979-8-3503-9678-2 -
                      doi:10.1109/ISGTEUROPE56780.2023.10407112},
      booktitle     = {2023 IEEE PES Innovative Smart Grid
                       Technologies Europe (ISGT EUROPE) :
                       [Proceedings] - IEEE, 2023. - ISBN
                       979-8-3503-9678-2 -
                       doi:10.1109/ISGTEUROPE56780.2023.10407112},
      abstract     = {Accurate forecasts of electricity prices are crucial for
                      the management of electric power systems and the development
                      of smart applications. European electricity prices have
                      risen substantially and became highly volatile after the
                      Russian invasion of Ukraine, challenging established
                      forecasting methods. Here, we present a Long Short-Term
                      Memory (LSTM) model for the German-Luxembourg day-ahead
                      electricity prices addressing these challenges. The
                      recurrent structure of the LSTM allows the model to adapt to
                      trends, while the joint prediction of both mean and standard
                      deviation enables a probabilistic prediction. Using a
                      physics-inspired approach–superstatistics–to derive an
                      explanation for the statistics of prices, we show that the
                      LSTM model faithfully reproduces both prices and their
                      volatility.},
      month         = {Oct},
      date          = {2023-10-23},
      organization  = {2023 IEEE PES Innovative Smart Grid
                       Technologies Europe (ISGT EUROPE),
                       Grenoble (France), 23 Oct 2023 - 26 Oct
                       2023},
      cin          = {IEK-10},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {1121 - Digitalization and Systems Technology for
                      Flexibility Solutions (POF4-112) / HGF-ZT-I-0029 - Helmholtz
                      UQ: Uncertainty Quantification - from data to reliable
                      knowledge (HGF-ZT-I-0029) / DFG project 491111487 -
                      Open-Access-Publikationskosten / 2022 - 2024 /
                      Forschungszentrum Jülich (OAPKFZJ) (491111487)},
      pid          = {G:(DE-HGF)POF4-1121 / G:(DE-Ds200)HGF-ZT-I-0029 /
                      G:(GEPRIS)491111487},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1109/ISGTEUROPE56780.2023.10407112},
      url          = {https://juser.fz-juelich.de/record/1025665},
}