Resilience Improvement Strategy for the Electrification-Transportation Coupling Network Based on Safe Deep Reinforcement Learning

[Objective] To address the problems that when large-scale electrification-transportation coupling network （ETCN） encounters sudden resilience faults， traditional schemes have slow generation speed， are difficult to respond to dynamic information interaction in real time， and artificial intelligence...

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Hlavní autor:	XU Ding, YANG Qiming, WU Mingming, FU Chaoran, XING Qiang, ZHANG Guoli, WANG Mingshen
Médium:	Artigo
Jazyk:	Chinês
Vydáno:	Editorial Department of Electric Power Construction 2026-03-01
Edice:	Dianli jianshe
Témata:	electrification-transportation coupling network\|resilience improvement strategy\|safe deep reinforcement learning （sdrl）\|hierarchical decision-making model\|modified rainbow algorithm
On-line přístup:	https://www.cepc.com.cn/fileup/1000-7229/PDF/1772431746240-136204125.pdf
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Resilience Improvement Strategy for the Electrification-Transportation Coupling Network Based on Safe Deep Reinforcement Learning

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