PowerMistral: A data-efficient wind power forecasting framework leveraging pre-trained large language models

Applied Energy 2026

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Authors: Qinglin Meng, Yuan Gao, Ying He, Sheharyar Hussain, Jinghang Lu, Yahui Chen, Chao Qin, Fengzhang Luo, Josep M. Guerrero

DOI: 10.1016/j.apenergy.2026.127625

Cited by: 29

References: 36

Fields of Study & Subjects

Energy Load and Power Forecasting Thermal Analysis in Power Transmission Topic Modeling

References 36