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Enhancing South Africa’s power grid management with AI: deep learning models for short-term forecasting of Eskom’s renewable generation under weather uncertainty

Crossref DOI link: https://doi.org/10.1007/s44379-026-00061-3

Published Online: 2026-03-31

Published Print: 2026-06

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Xelibokwe, Gift Katlego

Arreyndip, Nkongho Ayuketang

Ebobenow, Joseph

Afungchui, David
License Information

Text and Data Mining valid from 2026-03-31

Version of Record valid from 2026-03-31
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Article History

Received: 19 November 2025

Accepted: 25 March 2026

First Online: 31 March 2026

Declarations

:

: The authors declare no competing interests.

: All the analyses and plots have been generated exclusively by the authors. No graphs, plots or materials have been taken from anywhere without permission or references.

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