考虑可再生能源协调出力的电动汽车充电定价方法  

CHARGING PRICING METHOD OF ELECTIC VEHICLE CONSIDERING COORDIRATIED OUTPUT OF RENEWABLE ENERGY

作　　者：陆斯悦 及洪泉 张禄[1] 徐蕙 王培祎 Lu Siyue;Ji Hongquan;Zhang Lu;Xu Hui;Wang Peiyi(State Grid Beijing Electric Power Company,Beijing 100075,China)

机构地区：[1]国网北京市电力公司,北京100075

出　　处：《计算机应用与软件》2024年第9期383-390,397,共9页Computer Applications and Software

基　　金：国家电网公司科技项目(52020119000C)。

摘　　要：在一个配电网和城市交通网耦合框架中,提出一种电动汽车充电定价方法。建立以社会总成本最小为目标的电动汽车充电服务费的双层优化模型,模型上层为在含风电的配电网中求解充电服务费(Charging Service Fees, CSF)的二阶锥问题;下层为一个遵循用户均衡(User Equilibrium, UE)原则的交通分配问题。该模型考虑了风电输出和OD交通流的不确定性,建立基于深度强化学习的求解框架,对随机双层问题进行解耦和近似求解。以5节点系统和某城市交通-电力耦合网为例,验证了该模型的有效性。A charging pricing method for electric vehicles is proposed in a coupling framework of distribution network and urban transportation network.In this paper,a two-level optimization model for charging service charge of electric vehicles was established with the objective of minimizing the total social cost.The upper layer of the model was to solve the second-order cone problem of charging service fees(CSF)in the distribution network with wind power,and the lower level was a traffic assignment problem following the user equilibrium(UE)principle.Considering the uncertainty of wind power output and OD traffic flow,a solution framework based on deep reinforcement learning was established to decouple and approximate solve the stochastic bilevel problem.The effectiveness of the model is verified by a 5-bus system and a city traffic power coupling network.

关 键 词：深度强化学习 配电网 交通网 电动汽车充电费用 交通用户均衡 

分 类 号：TM73[电气工程—电力系统及自动化] TP39[自动化与计算机技术—计算机应用技术]