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

Kariniotakis, George and Camal, Simon and Sossan, Fabrizio and Nouri, Bijan and Lezaca Galeano, Jorge Enrique and Lange, Matthias and Alonso, Bastien and Libois, Quentin and Pinson, Pierre and Bessa, Ricardo and Goncalves, Carla (2022) Data Science for Next Generation Renewable Energy Forecasting - Highlight Results from the Smart4RES Project. In: 11th Solar and Storage Power System Integration Workshop, SIW 2021, 2021, pp. 181-184. IEEE Institution of Engineering and Technology. 11th Solar & Storage Power System Integration Workshop (SIW 2021), 2021-09-28, Berlin, Germany. doi: 10.1049/icp.2021.2499. ISBN 978-183953680-9. ISSN 2732-4494.

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Abstract

Smart4RES is a European Horizon2020 project developing next generation solutions for renewable energy forecasting. 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.

Item URL in elib:https://elib.dlr.de/190482/
Document Type:Conference or Workshop Item (Speech)
Title:Data Science for Next Generation Renewable Energy Forecasting - Highlight Results from the Smart4RES Project
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kariniotakis, GeorgeARMINESUNSPECIFIEDUNSPECIFIED
Camal, SimonARMINESUNSPECIFIEDUNSPECIFIED
Sossan, FabrizioARMINESUNSPECIFIEDUNSPECIFIED
Nouri, BijanUNSPECIFIEDhttps://orcid.org/0000-0002-9891-1974UNSPECIFIED
Lezaca Galeano, Jorge EnriqueUNSPECIFIEDhttps://orcid.org/0000-0001-5513-7467UNSPECIFIED
Lange, MatthiasEMSYSUNSPECIFIEDUNSPECIFIED
Alonso, BastienMétéo-FranceUNSPECIFIEDUNSPECIFIED
Libois, QuentinMétéo-FranceUNSPECIFIEDUNSPECIFIED
Pinson, PierreTechnical University of DenmarkUNSPECIFIEDUNSPECIFIED
Bessa, RicardoINESCTECUNSPECIFIEDUNSPECIFIED
Goncalves, CarlaINESCTECUNSPECIFIEDUNSPECIFIED
Date:9 May 2022
Journal or Publication Title:11th Solar and Storage Power System Integration Workshop, SIW 2021
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:2021
DOI:10.1049/icp.2021.2499
Page Range:pp. 181-184
Publisher:IEEE Institution of Engineering and Technology
ISSN:2732-4494
ISBN:978-183953680-9
Status:Published
Keywords:Renewable energy sources, Forecasting, Data science
Event Title:11th Solar & Storage Power System Integration Workshop (SIW 2021)
Event Location:Berlin, Germany
Event Type:international Conference
Event Date:28 September 2021
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:Digitalisation
DLR - Program:D - no assignment
DLR - Research theme (Project):D - no assignment, E - Condition Monitoring
Location: Oldenburg
Institutes and Institutions:Institute of Solar Research > Qualification
Institute of Networked Energy Systems > Energy Systems Analysis, OL
Deposited By: Lezaca Galeano, Dr. Jorge Enrique
Deposited On:23 Dec 2022 09:50
Last Modified:18 Feb 2025 10:14

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