An optimal scheduling strategy of a microgrid with v2g based on deep q-learning

HIGHLIGHTS

  • who: Yuxin Wen et al. from the School of Electrical Engineering and Automation, Wuhan University, Wuhan, China have published the research work: An Optimal Scheduling Strategy of a Microgrid with V2G Based on Deep Q-Learning, in the Journal: Sustainability 2022, 14, 10351. of /2022/
  • what: In , the model of reinforcement learning agent is applied to a microgrid system with distributed energy, which can formulate the optimal strategy for energy management and load scheduling among the three main bodies of a power source, distributed energy storage and user. The dispatch strategy of this paper is . . .

     

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