An LSTM-based multi-agent RL approach with decentralized execution and a dense reward reduces charging cost and unfinished charging demand in a simulated EV charging station under partial charger faults.
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Agent-Based Decentralized Energy Management of EV Charging Station with Solar Photovoltaics via Multi-Agent Reinforcement Learning
An LSTM-based multi-agent RL approach with decentralized execution and a dense reward reduces charging cost and unfinished charging demand in a simulated EV charging station under partial charger faults.