Short-term charging load prediction study of electric vehicle charging stations based on K-Medoids clustering and multi-factor optimization decomposition
Abstract The strong randomness and high volatility of electric vehicle charging behaviour make the accuracy of short-term charging load prediction at charging stations low. Effective electric vehicle charging station charging load prediction is the key to fully and reasonably increase the utilisatio...
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| Autori principali: | , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Portfolio
2025-10-01
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| Serie: | Scientific Reports |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1038/s41598-025-13180-3 |
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