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电动汽车的有序充电管理及其对配电网的影响分析 被引量:5

Research on Orderly Charging Management of Electric Vehicles and Its Impact on Distribution Network
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摘要 电动汽车以无序充电方式接入配电网时与网内基础用电负荷叠加,会形成峰上加峰的现象,不利于配电网的稳定运行。针对上述问题,首先对私家车充电负荷进行建模,采用蒙特卡罗抽样模拟电动汽车无序行为下的充电负荷曲线。然后提出一种新型的多时段动态充电价格机制,引导车主有序充电,并以配电网负荷波动最小为目标函数,优化电动汽车充电行为。最后在IEEE33节点配电网中,分别分析有序和无序充电负荷并网时电动汽车充电费用、配电网电压偏移率及网损,结果表明所提策略可有效兼顾用户利益和配电网的稳定运行。 When the electric vehicle is connected to the distribution network in a disorderly charging manner, it overlaps with the basic electricity load in the network.It will form a phenomenon of “peaks on top of peaks”,which is not conducive to the stable operation of the distribution network. According to the above problems, it firstly models the charging load of private cars, and uses Monte Carlo sampling to simulate the charging load curve under the disordered behavior of electric vehicles. Then, a new multi-period dynamic charging price mechanism is proposed to guide car owners to charge in an orderly manner, and takes the minimum load fluctuation of the distribution network as the objective function to optimize the charging behavior of electric vehicles.Finally, in the IEEE33 node distribution network, the charging cost of electric vehicles, the voltage bias of the distribution network when orderly and disorderly charging loads are connected to the grid are analyzed respectively. The results show that the proposed strategy can effectively take into account the interests of users and the stable operation of the distribution network.
作者 于瀛涵 陈嘉德 韩子娇 苑舜 马卓 YU Yinghan;CHEN Jiade;HAN Zijiao;YUAN Shun;MA Zhuo(College of Electrical Engineering,Shenyang University of Technology,Shenyang,Liaoning 110870,China;State Grid Liaoning Electric Power Co.,Ltd􀆰,Shenyang,Liaoning 110006,China;Northeast Regulatory Bureau of National Energy Administration,Shenyang,Liaoning 110006,China)
出处 《东北电力技术》 2023年第2期34-39,共6页 Northeast Electric Power Technology
关键词 电动汽车 配电网 多时段动态充电价格 电压偏移 网损 electric vehicle distribution network multi-period dynamic charging price voltage excursion network loss
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