Towards a paradigm of explainable AI applied in energy meteorology

Autor: Konstantinos Parginos, George Kariniotakis, Ricardo Bessa, Simon Camal

Publikováno v: EGU General Assembly 2023
EGU General Assembly 2023, EGU-European Geosciences Union, Apr 2023, Vienna, Austria. ⟨10.5194/egusphere-egu23-13992⟩

Standard practice of decision-making in energy systems relies largely on complex modeling chains to address technical constraints and integrate numerous sources of uncertainty. The increased penetration of Renewable Energy Sources (RES) such as solar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a4cc4357f1609f14111b15f68ea6116
https://hal.science/hal-04076558

Towards seamless and high-resolution renewable energy forecasting by the combination of approaches and data sources

Autor: Simon Camal, Dennis Van Der Meer, George Kariniotakis

Operational forecasting models of Renewable Energy Sources (RES) are usually developed for specific time frames, using a reduced set of data sources as a function of the forecasting horizon. This results in discontinuities in predictions between the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9eded9cd9c47e37180d7c993f8afa0c5
https://doi.org/10.5194/ems2022-534

End-to-end Learning for Hierarchical Forecasting of Renewable Energy Production with Missing Values

Autor: Akylas Stratigakos, Dennis van der Meer, Simon Camal, Georges Kariniotakis

Publikováno v: 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022
17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Jun 2022, Manchester-Online, United Kingdom. ⟨10.1109/PMAPS53380.2022.9810610⟩

International audience; Power systems feature an inherent hierarchical structure. Ensuring that forecasts across a hierarchy are coherent presents an important challenge in energy forecasting. In this context, proposed reconciliation or end-to-end le

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97810ed5a8d5af769d6dbd95b0c6bfef
https://hal.science/hal-03527644v3/file/v2_Hierachical_Forecasting.pdf

Forecasting regional wind production based on weather similarity and site clustering for the EEM20 Competition

Autor: Kevin Bellinguer, Valentin Mahler, Simon Camal, Georges Kariniotakis

Publikováno v: 40th International Symposium on Forecasting
40th International Symposium on Forecasting, International Institute of Forecasters, Oct 2020, Virtual Event, Brazil
HAL

International audience; Precise probabilistic forecasting tools of wind power generation are essential for solving problems related to the impact of wind generation uncertainty on electrical systems. In this context, the International Conference on t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::111852751e48ac2c50614e923eb1d687
https://hal.science/hal-03157849

Smart4RES: Towards next generation forecasting tools of renewable energy production

Autor: Stefan Wilbert, George Sideratos, Efrosyni Korka, Quentin Libois, Simon Camal, Alexandre Neto, Ganesh Sauba, Pierre Pinson, Remco Verzijlbergh, Gregor Giebel, Bijan Nouri, Matthias Lange, Ricardo J. Bessa, Stéphanie Petit, Raphaël Legrand, Georges Kariniotakis

The aim of this paper is to present the objectives, research directions and first highlight results of the Smart4RES project, which was launched in November 2019, under the Horizon 2020 Framework Programme. Smart4RES is a research project that aims t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce15540d3b2579a8bbabb7ba6c6e847c
https://hal.science/hal-02887072