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All-sky imager based irradiance nowcasts: combining a physical and a deep learning model

Fabel, Yann and Nouri, Bijan and Wilbert, Stefan and Blum, Niklas and Zarzalejo, L. F. and Pitz-Paal, Robert (2022) All-sky imager based irradiance nowcasts: combining a physical and a deep learning model. ISES. [Other]

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Official URL: https://www.ises.org/sites/default/files/2022-12/Presentation_Bijan%20Nouri.pdf

Abstract

Improved solar irradiance nowcasts based on all-sky imagers. Hybrid physical and end-to-end machine learning (ML) model. The ML model is based on an multi-modal deep learning model combining an vision transformer (for images) with an time series transformer (for time series data). Skill score improvements >12% points are achieved. Correct detection of cloud ramp rates improved by >8% points.

Item URL in elib:https://elib.dlr.de/192515/
Document Type:Other
Title:All-sky imager based irradiance nowcasts: combining a physical and a deep learning model
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Fabel, YannUNSPECIFIEDhttps://orcid.org/0000-0002-1892-5701UNSPECIFIED
Nouri, BijanUNSPECIFIEDhttps://orcid.org/0000-0002-9891-1974UNSPECIFIED
Wilbert, StefanUNSPECIFIEDhttps://orcid.org/0000-0003-3573-3004UNSPECIFIED
Blum, NiklasUNSPECIFIEDhttps://orcid.org/0000-0002-1541-7234UNSPECIFIED
Zarzalejo, L. F.UNSPECIFIEDhttps://orcid.org/0000-0003-4522-6815UNSPECIFIED
Pitz-Paal, RobertUNSPECIFIEDhttps://orcid.org/0000-0002-3542-3391UNSPECIFIED
Date:December 2022
Journal or Publication Title:Webinar beim Internation Solar Energy Society (ISES)
Refereed publication:No
Open Access:Yes
Publisher:ISES
Series Name:IEA PVPS Task 16 - All Sky Imagers Benchmarking
Status:Published
Keywords:Hybrid nowcasting model, Transformer, Deep learning, All-sky imager
HGF - Research field:Energy
HGF - Program:Materials and Technologies for the Energy Transition
HGF - Program Themes:High-Temperature Thermal Technologies
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Condition Monitoring
Location: Köln-Porz
Institutes and Institutions:Institute of Solar Research > Qualification
Deposited By: Nouri, Bijan
Deposited On:23 Dec 2022 09:54
Last Modified:28 Feb 2023 08:46

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