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Federated Heterogeneous-Agent Reinforcement Learning for the Flexible Dispatch of Energy Hubs

Energy hubs (EHs) are important district multi-energy systems that integrate various carriers for energy conversion and storage. For the flexible dispatch of EHs, reinforcement learning (RL) has been a promising solution, capable of effectively and efficiently handling inherent uncertainties within EHs. However, the sa...

Hao-Yuan Deng, Ling-Yu Chen, Wen-Bo Zeng et al. · 0 citations
Book Open access Aug 2026

GODM: Graph Orthogonal Diffusion Models for Spatio-Temporal Forecasting

A novel framework (GODM) is proposed that adopts orthogonalization to decouple intricate temporal dynamics while employing spatial convolutions to simulate information flow across space and consistently outperforms state-of-the-art spatio-temporal diffusion models.

Zhixian Wang, Michel Ferreira Cardia Haddad, J. E. Medina Reyes et al. · 0 citations

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