The invention discloses an electric vehicle charging station charging power distribution method based on deep reinforcement learning, and the method is characterized in that the method comprises the following steps: 1, screening a proper charging station for a user according to the position of the charging station, and the initial electric quantity and position of an electric vehicle, and obtaining a charging station candidate solution set of the electric vehicle; step 2, selecting to distribute the electric vehicle to the charging station with the lowest load according to the space load balance, and giving an optimal charging station by combining the time when the electric vehicle arrives at the charging station; step 3, according to the information of the electric vehicle arriving at the charging station, converting an electric vehicle charging resource allocation problem into a Markov process problem; and step 4, iteratively solving a Markov process problem by using a deep reinforcement learning algorithm, and taking a final action value as a final power distribution mode. The method can effectively reduce the charging cost of the user and the load gap of the power distribution network, and is beneficial to load balancing among multiple power distribution networks.

    本发明公开了一种基于深度强化学习的电动汽车充电站充电功率分配方法,其特征在于,包括如下步骤:步骤1、根据充电站的位置、电动汽车的初始电量和位置,为用户筛选出合适的充电站,从而得到电动汽车的充电站候选解集合;步骤2、根据空间负载均衡选择将电动汽车分配到负载最低的充电站,并结合电动汽车到达充电站的时间给出最优充电站;步骤3、根据到达充电站内的电动汽车的信息,将电动汽车充电资源分配问题转化为马尔可夫过程问题;步骤4、利用深度强化学习算法迭代求解马尔可夫过程问题,从而最终的动作值作为最终的功率分配方式。该方法可以有效的减少用户的充电成本和配电网的负载差距,有利于多配电网之间的负载均衡。


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    Titel :

    Electric vehicle charging station charging power distribution method based on deep reinforcement learning


    Weitere Titelangaben:

    基于深度强化学习的电动汽车充电站充电功率分配方法


    Beteiligte:
    XIA YONGXIANG (Autor:in) / CHENG ZHONGYI (Autor:in) / ZHANG JIAQI (Autor:in)

    Erscheinungsdatum :

    04.04.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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