Multi-agent DRL-based data-driven approach for PEVs charging/discharging scheduling in smart grid

DOI10.1016/J.JFRANKLIN.2022.01.016OpenAlexW4210584255MaRDI QIDQ2667469

Yanyan Li

Publication date: 4 March 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2022.01.016

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Related Items (2)

Asynchronous deep reinforcement learning with gradient sharing for state of charge balancing of multiple batteries in cyber-physical electric vehicles ⋮ Improved DRL-based energy-efficient UAV control for maximum lifecycle

Cites Work

• Kernel-based reinforcement learning
• Self-scheduling of electric vehicles in an intelligent parking lot using stochastic optimization
• Energy management of plug-in hybrid electric vehicles with unknown trip length
• A novel combinatorial optimization algorithm for energy management strategy of plug-in hybrid electric vehicle

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