An Adaptive Transfer Learning Approach for Dynamic Demand Response Potential Prediction of Load Aggregators

Accurate forecasting of aggregated demand response (DR) potential is critical for load aggregators, yet remains challenging under severe data scarcity and domain shift conditions. This paper proposes a domain-adaptive transfer learning framework based on an ensemble of Random Vector Functional-Link...

全面介绍

书目详细资料

Principais autores:	Dongli Jia, Huiyu Zhan, Keyan Liu, Kunhang Xie, Bin Gou
格式:	Artigo
语言:	Inglês
出版:	MDPI AG 2026-02-01
丛编:	Energies
主题:	demand response potential load aggregator transfer learning domain adaptation random vector functional-link network data scarcity
在线阅读:	https://www.mdpi.com/1996-1073/19/4/1083
标签:	添加标签 没有标签, 成为第一个标记此记录!