Collaborative Forecasting of Multiple Energy Loads in Integrated Energy Systems Based on Feature Extraction and Deep Learning

Accurate load forecasting is crucial for the safe, stable, and economical operation of integrated energy systems. However, directly applying single models to predict coupled cooling, heating, and electric loads under complex influencing factors often yields unsatisfactory results. This paper propose...

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Detalhes bibliográficos

Principais autores:	Zhe Wang, Jiali Duan, Fengzhang Luo, Xiaoyu Qiu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2025-02-01
coleção:	Energies
Assuntos:	integrated energy system load forecasting empirical mode decomposition k-medoids clustering multi-task learning
Acesso em linha:	https://www.mdpi.com/1996-1073/18/5/1048
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