The invention discloses an electric vehicle charging strategy generation method and device, equipment and a storage medium, which are used for solving the technical problem that the existing electric vehicle charging management needs manual intervention or complex equipment deployment and is difficult to meet the scene requirement of large-scale popularization. The method comprises the following steps: collecting residual electric quantity of the electric vehicle and electricity price data of each time period; taking the battery remaining capacity and the electricity price data as states, taking battery charging and discharging power as a decision, and combining a reward function and a state transfer function to construct a Markov decision process of the electric vehicle; a deep reinforcement learning model is constructed by taking the balance between the maximized expected return and entropy as an optimization target and combining the Markov decision process; and solving the deep reinforcement learning model to obtain a charging strategy of the electric vehicle.
本发明公开了一种电动汽车充电策略生成方法、装置、设备及存储介质,用于解决现有的电动汽车充电管理需要人工干预或者复杂设备部署,难以满足大规模普及的场景需求的技术问题。本发明包括:采集电动汽车的剩余电量及各时间段的电价数据;以所述电池剩余电量和所述电价数据为状态、以电池充放电功率为决策,结合奖励函数和状态转移函数构建所述电动汽车的马尔可夫决策过程;以最大化预期回报和熵之间的权衡为优化目标,结合所述马尔可夫决策过程,构建深度强化学习模型;求解所述深度强化学习模型,得到所述电动汽车的充电策略。
Electric vehicle charging strategy generation method and device, equipment and storage medium
一种电动汽车充电策略生成方法、装置、设备及存储介质
2024-06-14
Patent
Electronic Resource
Chinese
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