Post-Disaster Generation Dispatching for Enhanced Resilience: A Multi-Agent Deep Deterministic Policy Gradient Learning Approach

This paper proposes a reinforcement learning-based approach for dispatching distributed generators (DGs) to enhance operational resilience of electric distribution systems after a severe outage event. The increased computational complexities and sophisticated modeling procedure of resilience-based e...

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Vydané v:	North American Power Symposium (Online) s. 1 - 6
Hlavní autori:	Abdelmalak, Michael, Hosseinpour, Hadis, Hotchkiss, Eliza, Ben-Idris, Mohammed
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.10.2022
Predmet:	Computational modeling Dispatching Distribution system extreme weather events Generators Power supplies Real-time systems Reinforcement learning resilience Training
ISSN:	2833-003X
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