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Short-term charging load prediction study of electric vehicle charging stations based on K-Medoids clustering and multi-factor optimization decomposition

Crossref DOI link: https://doi.org/10.1038/s41598-025-13180-3

Published Online: 2025-10-15

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

Authors

Li, Hanting

Tang, Minan

Cao, Jie

Yang, Tong

Wang, Changyou

Jiang, Yude
Funding

Funding for this research was provided by:

Gansu Provincial Department of Education: Excellent Graduate Student “Innovation Star” Project (2025CXZX-662)

National Natural Science Foundation of China (62363022)

Natural Science Foundation of Gansu Province (23JRRA886)

Gansu Provincial Department of Education: Industrial Support Plan Project (2023CYZC-35)
License Information

Text and Data Mining valid from 2025-10-15

Version of Record valid from 2025-10-15
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Article History

Received: 24 February 2025

Accepted: 22 July 2025

First Online: 15 October 2025

Declarations

:

: The authors declare no competing interests.

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