Game theory-based electricity pricing and microgrids management using online deep reinforcement learning

This study addresses a bi-level problem involving a retailer and multiple residential microgrids. The retailer, at the upper level, disseminates selling and buying electricity price signals to maximize profit, while microgrid agents, at the lower level, manage their resources based on these signals...

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Vydané v:	Applied soft computing Ročník 182; s. 113621
Hlavní autori:	Shademan, Mahdi, Azizi, Ali, Jadid, Shahram
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.10.2025
Predmet:	Deep reinforcement learning Demand response Fuzzy chance constrained programming Microgrids Model-drift Resource management Model-drift Fuzzy chance constrained programming Deep reinforcement learning Demand response Resource management Microgrids
ISSN:	1568-4946
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