Smart4RES: Next generation solutions for renewable energy forecasting and applications with focus on distribution grids

Simon Camal (1) , Georges Kariniotakis (1) , Fabrizio Sossan (1) , Quentin Libois (2) , Raphael Legrand (2) , Laure Raynaud (2) , Matthias Lange (3) , Annah Mehrens (3) , Pierre Pinson (4) , Amandine Pierrot (4) , Gregor Giebel (4) , Tufhe Göcmen (4) , Ricardo Bessa (5) , Jose Gouveia (5) , Luis Teixeira (5) , Alexandre Neto (6) , Ricardo Manuel Santos (6) , Gisela Mendes (6) , Bijan Nouri (7) , Jorge Lezaca (7) , Remco Verziljbergh (8) , Gerrit Deen (8) , George Sideratos (9) , Christos Vitellas (10) , Ganesh Sauba (11) , Marcel Eijgelaar (11) , Stéphanie Petit (12)

1 PERSEE - Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques
2 DIRSE - Météo-France Direction Interrégionale Sud-Est
3 EMSYS - Energy & Meteo Systems - energy
4 DTU - Danmarks Tekniske Universitet = Technical University of Denmark
5 INESC TEC - Institute for Systems and Computer Engineering, Technology and Science [Porto]
6 EDP New Energy World – Center for New Energy Technologies, EDP Distribuição
7 DLR - Deutsches Zentrum für Luft- und Raumfahrt
8 WHIFFLE
9 NTUA - National Technical University of Athens [Athens]
10 DEDDIE
11 DNV GL
12 Dowel Innovation

This paper presents the solutions on renewable energy forecasting proposed by the Horizon2020 Project Smart4RES. The ambition of the project is twofold: (1) increase substantially the performance of short-term forecasting models of Renewable Energy Sources (RES) production and associated weather forecasting and (2) optimize decisions subject to RES uncertainty in power systems and electricity markets. Developments are based on latest advances in meteorology and original use of data science (combination of multiple data sources, data-driven approaches for trading and grid management). Finally, solutions such as flexibility forecast of distributed resources and data markets are oriented towards value for power system stakeholders. Although the project covers a broad scope, in this paper we focus on a selection of use cases that concern the integration of renewables in distribution grids.

Mots clés: FORECASTING; RENEWABLE ENERGY; DISTRIBUTION GRIDS; ENERGY METEOROL-OGY; DATA SCIENCE; SMART GRID

Domaines: Energie électrique; Machine Learning [stat.ML]; Applications [stat.AP]; Optimisation et contrôle [math.OC]; Probabilités [math.PR]; Statistiques [math.ST]

Simon Camal, Georges Kariniotakis, Fabrizio Sossan, Quentin Libois, Raphael Legrand, et al.. Smart4RES: Next generation solutions for renewable energy forecasting and applications with focus on distribution grids. CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution, CIRED, Sep 2021, On line, Switzerland. pp.2899-2903, ⟨10.1049/icp.2021.1829⟩. ⟨hal-03531728⟩