2023/06/05 · This paper proposes a deep reinforcement learning (DRL)-based allocation approach that optimally and efficiently allocates the grid's commands to the EVs and ...

To tackle these challenges, this paper proposes a deep reinforcement learning (DRL)-based allocation approach that optimally and efficiently allocates the ...

Multi-agent deep reinforcement learning (MADRL) has been applied to EV charging scheduling. However, it relies on centralized training and thus is significantly ...

This paper aims to crack the individual EV charging scheduling problem considering the dynamic user behaviors and the electricity price by developing a ...

A prediction module is included in the DRL framework improve the foresight of the algorithm, and a safety module is designed to avoid unsafe actions.

An actor–critic learning-based smart charging algorithm (SCA) is developed to schedule the EV charging against the uncertainties in EV charging behaviors ...

2024/06/03 · A cooperative charging control strategy for electric vehicles based on multi-agent deep reinforcement learning.

The optimal and efficient EV charging control is modeled as a partially-observable constrained Markov decision process and solved by RL.

2023/11/20 · : EV charging command fast allocation approach based on deep reinforcement learning with safety modules. IEEE Trans. Smart Grid https://doi ...

Zhang, EV charging command fast allocation approach based on deep reinforcement learning with safety modules, IEEE Trans. Smart Grid, № 15, с. 757 https ...