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https://doi.org/10.5194/wes-20...
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
Copernicus Publications
Other literature type . 2024
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Analysis of a 30 GW offshore wind power scenario in Norway using time-series computed from numerical weather model data

Authors: Harald Georg Svendsen; John Olav Giæver Tande;

Analysis of a 30 GW offshore wind power scenario in Norway using time-series computed from numerical weather model data

Abstract

Abstract. This article investigates implications of integrating 30 GW offshore wind in Norway. Wind power time series for relevant locations are analysed using 30 years of hourly numerical weather model reanalysis data. The study presents key statistical properties of the wind power time series. The emphasis lies on correlation, geographical smoothing, and variability across different time scales. These findings hold significant relevance for the strategic planning of offshore wind farm development, and for effectively preparing the energy system to accommodate this extensive wind power deployment that would mean a doubling of the Norwegian electricity generation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid