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Satellite image-based generation of high frequency solar radiation time series for the assessment of solar energy systems

Schreck, Sebastian und Schroedter-Homscheidt, Marion und Klein, Martin und Cao, Karl-Kien (2020) Satellite image-based generation of high frequency solar radiation time series for the assessment of solar energy systems. Meteorologische Zeitschrift. Borntraeger Science Publishers. doi: 10.1127/metz/2020/1008. ISSN 0941-2948.

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Offizielle URL: http://dx.doi.org/10.1127/metz/2020/1008

Kurzfassung

Solar energy is envisaged as a major pillar of the global transition to a climate-friendly energy system. Variability of solar radiation requires additional balancing measures to ensure a stable and secure energy supply. In order to analyze this issue in detail, solar radiation time series data of appropriate temporal and spatial resolution is necessary. Common weather models and satellites are only delivering solar surface irradiance with temporal resolutions of up to 15 min. Significant short-term variability in irradiances within seconds to minutes however is induced by clouds. Ground-based measurements typically used to capture this variability are costly and only sparsely available. Hence, a method to synthetically generate time series from currently available satellite imagery is of value for researchers, grid operators, and project developers. There are efforts to increase satellite resolution to 1 min, but this is not planned everywhere and will not change the spatial resolution. Therefore, the fundamental question remains if there are alternative strategies to obtain high temporal resolution observations at a pinpoint. This paper presents a method to generate 1 min resolved synthetic time series of global and direct normal irradiances for arbitrary locations. A neural network based on satellite image derived cloud structure parameters enables to classify high-frequency solar radiation variability. Combined with clear-sky radiation data, 1 min time series which reflect the typical variability characteristics of a site are reproduced. Testing and validation against ground observations (BSRN) show that the method can accurately reproduce characteristics such as frequency and ramp distributions. An application case demonstrates the usage in low-voltage grid studies.

elib-URL des Eintrags:https://elib.dlr.de/135581/
Dokumentart:Zeitschriftenbeitrag
Titel:Satellite image-based generation of high frequency solar radiation time series for the assessment of solar energy systems
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schreck, Sebastianschreck.sh (at) gmail.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Schroedter-Homscheidt, Marionmarion.schroedter-homscheidt (at) dlr.dehttps://orcid.org/0000-0002-1854-903XNICHT SPEZIFIZIERT
Klein, MartinM.Klein (at) dlr.dehttps://orcid.org/0000-0001-7283-4707NICHT SPEZIFIZIERT
Cao, Karl-KienKarl-Kien.Cao (at) dlr.dehttps://orcid.org/0000-0002-9720-0337NICHT SPEZIFIZIERT
Datum:13 Mai 2020
Erschienen in:Meteorologische Zeitschrift
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.1127/metz/2020/1008
Verlag:Borntraeger Science Publishers
ISSN:0941-2948
Status:veröffentlicht
Stichwörter:Solar radiation variability, 1 min time series, neural networks, synthetic time series, distribution grid, voltage violations
HGF - Forschungsbereich:Energie
HGF - Programm:TIG Technologie, Innovation und Gesellschaft
HGF - Programmthema:Erneuerbare Energie- und Materialressourcen für eine nachhaltige Zukunft
DLR - Schwerpunkt:Energie
DLR - Forschungsgebiet:E SY - Energiesystemanalyse
DLR - Teilgebiet (Projekt, Vorhaben):E - Systemanalyse und Technikbewertung (alt)
Standort: Stuttgart
Institute & Einrichtungen:Institut für Technische Thermodynamik > Energiesystemanalyse
Institut für Vernetzte Energiesysteme > Energiesystemanalyse
Hinterlegt von: Cao, Dr.-Ing. Karl-Kien
Hinterlegt am:04 Aug 2020 15:23
Letzte Änderung:24 Okt 2023 14:16

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