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Better seasonal forecasts for the renewable energy industry

descriptionPublicationkeyboard_double_arrow_right Article , Journal 17 Feb 2020 Spain Publisher:Springer Science and Business Media LLCJournal:Nature Energy, volume 5, pages 108-110 (eissn: 2058-7546,

Authors: Anton Orlov; Jana Sillmann; Ilaria Vigo;

doi: 10.1038/s41560-020-0561-5

handle: 2117/328210

Better seasonal forecasts for the renewable energy industry

- Summary
- Subjects
- Metrics

Abstract

Anomalous seasons such as extremely cold winters or low-wind summers can seriously disrupt renewable energy productivity and reliability. Better seasonal forecasts providing more accurate information tailored to stakeholder needs can help the renewable energy industry prepare for such extremes. The authors acknowledge funding from the EU Horizon 2020 project “Sub-seasonal to seasonal climate forecasting for energy (S2S4E)” (GA776787). Peer Reviewed

Country

Spain

Related Organizations

Universitat Politècnica de Catalunya
Spain
Universitat Polite`cnica de Catalunya
Spain
Barcelona Supercomputing Center
Spain

Keywords

Energy industries, Indústries energètiques, :Energies [Àrees temàtiques de la UPC], Anomalous seasons, Renewable energy sources, Projection and prediction, Àrees temàtiques de la UPC::Energies, Climate change, Energy management, Renewable energies, Climatic changes, Seasonal variability, Energies renovables, Seasonal forecast, Canvis climàtics

Impact byBIP!

	citations 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).	73
	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.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%