Optimal scheduling for charging and discharging of electric vehicles based on deep reinforcement learning

Optimal scheduling for charging and discharging of electric vehicles based on deep reinforcement learning

The growing scale of electric vehicles (EVs) brings continuous challenges to the energy trading market. In the process of grid-connected charging of EVs, disorderly charging behavior of a large number of EVs will have a substantial impact on the grid load. Aiming to solve the problem of optimal sche...

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Bibliographic Details
Main Authors: Dou An, Feifei Cui, Xun Kang
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Energy Research
Subjects:
electric vehicles (EVs)
deep reinforcement learning
partially observable markov decision process (PODMP)
multi-agent deep deterministic policy gradient (MADDPG)
long short-term memory (LSTM)
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2023.1273820/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2023.1273820/full

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