A novel multi-objective optimization based multi-agent deep reinforcement learning approach for microgrid resources planning

Abid, Md. Shadman; Apon, Hasan Jamil; Hossain, Salman; Ahmed, Ashik; Ahshan, Razzaqul; Lipu, M.S. Hossain

doi:10.1016/j.apenergy.2023.122029

Applied Energy

2024

DOI: 10.1016/j.apenergy.2023.122029

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A novel multi-objective optimization based multi-agent deep reinforcement learning approach for microgrid resources planning

Md. Shadman Abid,

Hasan Jamil Apon,

Salman Hossain

et al.

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Cited by 11 publications

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A novel multi-objective optimization based multi-agent deep reinforcement learning approach for microgrid resources planning

Cited by 11 publications

References 53 publications

A Novel Political Optimizer Integrated with ThingSpeak Platform for Multi-Objective Energy Management in Microgrids

A Novel Political Optimizer Integrated with ThingSpeak Platform for Multi-Objective Energy Management in Microgrids

Suppressing active power fluctuations at PCC in grid-connection microgrids via multiple BESSs: A collaborative multi-agent reinforcement learning approach

Cooperative optimal dispatch of multi-microgrids for low carbon economy based on personalized federated reinforcement learning

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