Enhancing electric vehicle charging load prediction in data-scarce scenarios: A hybrid deep learning-based approach integrating clustering analysis and transfer learning

Enhancing electric vehicle charging load prediction in data-scarce scenarios: A hybrid deep learning-based approach integrating clustering analysis and transfer learning

Accurate electric vehicle (EV) load forecasting is crucial for efficient grid operations and demand-side management, yet it is challenging in data-scarce scenarios. Transfer learning (TL) offers a solution by transferring knowledge from data-rich to data-limited scenarios. However, when the knowledg...

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Bibliographic Details
Main Authors: Rehman Zafar, Pei Huang, Yongjun Sun
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Energy and AI
Subjects:
EV load forecasting
Transfer learning
Fine tuning
BiLSTM
Deep learning
Clustering
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546825000771
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