RSynLLM: A risk-aware routing mixture-of-experts large language model for multi-energy load forecasting in large-scale distribution networks

Journal:

Applied Energy

Published:

2026-03-01

DOI:

10.1016/j.apenergy.2025.127227

Affiliations:

6

Authors:

8

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Institutions	Authors	Share
South China University of Technology (SCUT), China	5.666667	0.71
Wuhan University (WHU), China	1.000000	0.13
University of Denver, United States of America (USA)	1.000000	0.13
Guangdong Provincial Laboratory of Artificial Intelligence and Digital Economy, SZU, China	0.333333	0.04

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