SECURES-Met: A European meteorological data set suitable for electricity modelling applications.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
07 09 2023
07 09 2023
Historique:
received:
01
06
2023
accepted:
18
08
2023
medline:
11
9
2023
pubmed:
8
9
2023
entrez:
7
9
2023
Statut:
epublish
Résumé
The modelling of electricity production and demand requires highly specific and comprehensive meteorological data. One challenge is the high temporal frequency as electricity production and demand modelling typically is done with hourly data. On the other side the European electricity market is highly connected, so that a pure country-based modelling is not expedient and at least the whole European Union (EU) area has to be considered. Additionally, the spatial resolution of the data set must be able to represent the thermal conditions, which requires high spatial resolution at least in mountainous regions. All these requirements lead to huge data amounts for historic observations and even more for climate change projections for the whole 21
Identifiants
pubmed: 37679367
doi: 10.1038/s41597-023-02494-4
pii: 10.1038/s41597-023-02494-4
pmc: PMC10484998
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
590Informations de copyright
© 2023. Springer Nature Limited.
Références
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pubmed: 27357792
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pubmed: 32981975
Sci Data. 2023 Feb 22;10(1):103
pubmed: 36813797
Sci Data. 2023 Sep 7;10(1):590
pubmed: 37679367