Data science
for renewable
energy prediction

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The project

Smart4RES is a European collaborative R&D project funded under the H2020 programme. It aims to substantially improve the entire model and value chain in renewable energy prediction by proposing the next generation of RES forecasting models, enabling an increase of at least 15% in RES forecas- ting performance.

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The consortium

Led by ARMINES, the project gathers 12 partners from 6 European countries, with a recognised leadership along the modelling and forecasting ecosystem.

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Concept & methodology

A use case approach is adopted to describe Smart4RES requirements and to propose a common model for all configurations from the perspective of any Smart4RES tools‘ users.


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12 June 2023

News & Events

Smart4RES final conference: recordings available

Gathering above 90 participants from all over the world, the Smart4RES final conference tool place on the 14th of April in Paris, France.

The benefit of improved numerical weather predictions and LES models tailored for energy forecasts was presented by Quentin Libois from METEO FRANCE and Remco Verzijlbergh from Whiffle, following motivating speeches from our sponsor Institut Carnot M.I.N.E.S, Mattjis Soede of the European Commission, and Georges Kariniotakis, the Smart4RES Project Coordinator.

Another exciting development was using sky cameras network from German Aerospace Center (DLR) and lightning data for short-term forecasts. Matthias Lange from emsys showed how these new products are effective in situations with broken clouds, snow, fog or thunderstorms.

Tufhe Goçmen DTU Wind and Energy Systems presented how 4-beam LIDAR measurements can be used as a powerful tool to provide intra-minute wind power forecasting and higher accuracy of forecasts. To simplify RES forecasting over multiple time scales and handle the multi-source inputs, Dennis van der Meer – ARMINES introduced novel approaches for seamless multivariate probabilistic forecasting and online forecast combination, showing improvement of NWP component forecasts.

Ideas for creating a more open energy data market by incentivising data sharing and fostering innovation in renewable energy forecasting while preserving privacy were also presented by Pierre Pinson, Imperial College London, and Carla Gonçalves INESC TEC

Last but not least, prescriptive strategies integrating information about forecast uncertainty in different power system and electricity market use cases driven by decarbonization and resilience needs were presented by Ricardo Bessa, Dimitris Lagos, Simon Camal and Akylas Stratigakos.

Finally, the panel moderated by Gregor Giebel and George Kariniotakis proposed directions for future work and for enhanced implementation of research solutions. Ana García Gómez from EDP Renewables and Maxime FORTIN from RTE, provided the views and perspectives from the industry.

Recordings of the event are available from the Resource Center of the project website: