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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Autore principale:	Vahid M. Nik
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-05-01
Serie:	Energy and AI
Soggetti:	Adaptive reinforcement learning Heatwave Decentralized energy management Energy flexibility Climate resilience Weather forecast
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2666546826000881
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