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From peak shaving to stress redistribution: Emergent heatwave resilience through weather-informed decentralized reinforcement learning

Heatwaves increasingly challenge urban electricity networks by intensifying and reshaping cooling demand over extended periods. This study investigates how weather-informed Adaptive Reinforcement Learning for Energy Management (ARLEM), a decentralized model-free control framework, redistributes cool...

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Hovedforfatter: Vahid M. Nik
Format: Artigo
Sprog:Inglês
Udgivet: Elsevier 2026-05-01
Serier:Energy and AI
Fag:
Adaptive reinforcement learning
Heatwave
Decentralized energy management
Energy flexibility
Climate resilience
Weather forecast
Online adgang:http://www.sciencedirect.com/science/article/pii/S2666546826000881
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