The learning-based EMS framework and system design of LearningEMS. (IMAGE)
Caption
(a) It consists of three layers: the EV environment layer, the learning-based algorithm layer, and the application layer. D3QN: dueling DDQN; CQL: conservative Q-learning; BCQ: batch-Constrained Q-Learning; SB3: stable-Baselines3; RLlib: reinforcement learning library; (b) Training pipeline of LearningEMS: First, choose an EV environment, users can create new environments or add modules to existing ones. Then, select an algorithm and dataset. Finally, start training. After training the policy in simulation, it can be directly deployed into the controller, enabling hardware-in-the-loop (HIL) or vehicle-in-the-loop (VIL) experiments.
Credit
Yong Wang et al.
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