The invention relates to an electric vehicle intelligent charging optimization method and system based on a Monte Carlo method. The method comprises the steps of setting any strategy for all chargingconditions; setting an arbitrary initialization action value function value for all charging conditions s and actions a; substituting the state s0 and the action a0 at the starting moment into an initialization strategy to obtain a sequence; obtaining a G value corresponding to the condition si and the action ai at the moment i according to the sequence; if the state st and the action at appear inthe sequence, recording G values of the state st and the action at, traversing all to-be-tested states and actions, and obtaining G values corresponding to all states and actions appearing in the sequence; S6, averaging all G values to obtain an action value function value; repeating the steps, selecting different policies and obtaining action value function values corresponding to the policies;wherein the strategy corresponding to the maximum action value function value is the optimal strategy. The optimal charging scheme of the electric vehicle is given based on the Monte Carlo method, calculation is accurate, and efficiency is high.
本发明涉及一种基于蒙特卡洛方法的电动车智能充电优化方法和系统,包括:对所有的充电状况s设置一任意策略;对所有的充电状况s和行动a设置一任意初始化行动值函数值;将开始时刻的状态s0和行动a0带入初始化策略获得序列;根据上述序列获得i时刻状况si和行动ai对应的G值;若状态st和行动at在序列中出现过,则记录其G值中,遍历所有待测状态和行动,获得所有在序列中出现过的状态和行动对应的G值;S6将所有的G值取平均值获得行动值函数值;重复上述步骤,选取不同的策略并获得与其对应的行动值函数值;其中行动值函数值最大时对应的策略为最优策略。其基于蒙特卡洛方法给出了电动车的最优充电方案,计算准确,效率高。
Electric vehicle intelligent charging optimization method and system based on Monte Carlo method
一种基于蒙特卡洛方法的电动车智能充电优化方法和系统
2021-03-02
Patent
Elektronische Ressource
Chinesisch
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