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  •  E. Jahangir, Q. Libois, F. Couveux, B. Vié, D. Saint-Martin. Uncertainty of shortwave cloud radiative impact due to the parameterization of liquid cloud optical properties. Submitted to JAMES. 2021.
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  • Jack FoxErik ElaBen HobbsJustin SharpJosh NovacheckAmber MotleyRicardo J. BessaPierre PinsonGeorges Kariniotakis Forecasting and Market Design Advances: Supporting an Increasing Share of Renewable Energy, in IEEE Power and Energy Magazine, vol. 19, no. 6, pp. 77-85, Nov.-Dec. 2021, doi: 10.1109/MPE.2021.3104132. 
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  • George Kariniotakis, Simon Camal, Fabrizio Sossan, Bijan Nouri, Jorge Lezaca, Matthias Lange, Bastien Alonzo, Quentin Libois, Pierre Pinson, Ricardo Bessa, Carla Goncalves. Data Science for Next Generation Renewable Energy Forecasting – Highlight Results from the Smart4RES Project. Solar Integration Workshop, September 2021, Berlin, Germany.                Download the article.
  • Simon Camal, George Kariniotakis, Fabrizio Sossan, Quentin Libois, Raphael Legrand, Laure Raynaud, Matthias Lange, Annah Mehrens, Pierre Pinson,Amandine Pierrot, Gregor Giebel, Tufhe Göcmen, Ricardo Bessa, Jose Gouveia, Luis Teixeira, Alexandre Neto, Ricardo Manuel Santos, Gisela Mendes, Bijan Nouri ,Jorge Lezaca, Remco Verziljbergh, Gerrit Deen, George Sideratos, Christos Vitellas, Ganesh Sauba, Marcel Eijgelaar, Stéphanie Petit. Smart4RES: Next generation solutions for renewable energy forecasting and its applications for power distribution grids. CIRED 2021 Conference, September 2021, Geneva, Switzerland.
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  • Akylas Stratigakos, Simon Camal, Andrea Michiorri, Georges Kariniotakis. Prescriptive Trees for Integrated Forecasting and Optimization Applied in Trading of Renewable Energy. 2021. ⟨hal-03330017⟩
    Download the preprint in HAL.
  • Akylas Stratigakos, Andrea Michiorri, Georges Kariniotakis. A Value-Oriented Price Forecasting Approach to Optimize Trading of Renewable Generation. 2021 IEEE Madrid PowerTech, IEEE, Jun 2021, Madrid, Spain. ⟨hal-03208575⟩
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  • Amandine Pierrot and Pierre Pinson. Adaptive Generalized Logit-Normal Distributions for Wind Power Short-Term Forecasting. 2021 IEEE Madrid PowerTech, IEEE, Jun 2021, Madrid, Spain. eprint 2012.08910.
    Download the e-print in arXiv.
  • Fabel, Y., Nouri, B., Wilbert, S., Blum, N., Triebel, R., Hasenbalg, M., … & Pitz-Paal, R. Applying self-supervised learning for semantic cloud segmentation of all-sky images. Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2021-1, in review 2021.
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  • Blum, N. B., Nouri, B., Wilbert, S., Schmidt, T., Lünsdorf, O., Stührenberg, J., Heinemann, D., Kazantzidis, A., and Pitz-Paal, R. Cloud height measurement by a network of all-sky-imagers, Atmos. Meas. Tech. Discuss., 2020.
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  • Carla Gonçalves, Laura Cavalcante, Margarida Brito, Ricardo J. Bessa, João Gama. Forecasting Conditional Extreme Quantiles for Wind Energy, Electric Power Systems Research, 2021.
    Part of the Special Issue Proceedings of the 21st Power Systems Computation Conference (PSCC 2020).
    Published paper: https://doi.org/10.1016/j.epsr.2020.106636
  • Chiara Di Modica, Pierre Pinson, Souhaib Ben Taieb. Online forecast reconciliation in wind power prediction, Electric Power Systems Research, 2021.
    Part of the Special Issue Proceedings of the 21st Power Systems Computation Conference (PSCC 2020).
    Published paper: https://doi.org/10.1016/j.epsr.2020.106637