Published January 14, 2022 | Version v1
Conference paper Open

Data Science for Next Generation Renewable Energy Forecasting - Highlight Results from the Smart4RES Project

Creators

  • 1. MINES Paris - PSL University, Center PERSEE
  • 2. Deutsches Zentrum für Luft- und Raumfahrt (DLR)
  • 3. EMSYS Gmbh
  • 4. Meteo-France - CNRS, CNRM UMR 3589
  • 5. Technical University of Denmark (DTU)
  • 6. INESC TEC

Description

Smart4RES is a European Horizon2020 project developing next generation solutions for renewable energy forecast- ing. This paper presents highlight results obtained during the first year of the project. Data science is used throughout the proposed solutions in order to process the large amount of heterogeneous data available to forecasters, and derive model-free approaches of forecasting and decision-aid tasks. This paper presents a series of solutions addressing relevant for Photovoltaics (PV) and storage applications. High-resolution Numerical Weather Predictions and regional solar irradiance forecasting provide detailed information on local weather conditions and their variability. PV power forecasting benefits from such new data sources, but also the proposed collaborative data exchange. Finally, data-driven methods simplify decision-making for trading in short-term markets and for grid management.

Notes

This paper (presentation file) was presented at the 11th Solar & Storage Integration Workshop and published in the workshop's proceedings

Files

SolarIntegWorkshop2021_Smart4RES.pdf

Files (1.9 MB)

Name Size Download all
md5:bd69055309b13b262098c65a459c5c89
1.9 MB Preview Download

Additional details

Funding

Smart4RES – Next Generation Modelling and Forecasting of Variable Renewable Generation for Large-scale Integration in Energy Systems and Markets 864337
European Commission