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电动汽车充电站储能容量自动配置研究

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电动汽车充电站储能容量配置受到多个条件的约束,导致配置结果不能达到最优,所以研究基于改进入侵杂草算法的电动汽车充电站储能容量自动配置方法.计算电动汽车充电站光伏出力,结合计算结果估计电动汽车充电站负荷.根据负荷估计结果确定经济成本、储能电池的循环效率、变压器容量、功率等级和充电桩数量等多个约束条件,搭建电动汽车充电站储能容量自动配置目标函数,采用改进入侵杂草算法自动求解目标函数,获取全局最优解,实现电动汽车充电站储能容量自动配置.实验结果表明,所提方法的电动汽车充电站负荷估计精度更高,储能容量配置效果更佳,运行效率更高,配置结果具有可靠性.
Research on Automatic Configuration of Energy Storage Capacity in Electric Vehicle Charging Stations
The configuration of energy storage capacity in electric vehicle charging stations is constrained by multiple conditions,resulting in suboptimal configuration results.Therefore,an automatic configuration method for energy storage capacity in electric vehi-cle charging stations based on an improved invasive weed algorithm is studied.Calculate the photovoltaic output of the electric vehicle charging station and estimate the load of the electric vehicle charging station based on the calculation results.According to the result of load estimation,multiple constraints such as economic cost,cycle efficiency of energy storage battery,transformer capacity,power level and number of Charging station are determined,and the objective function of automatic configuration of energy storage capacity of electric vehicle charging station is established.The objective function is automatically solved by using the improved invasive weed algorithm to obtain the global optimal solution,so as to realize the automatic configuration of energy storage capacity of electric vehicle charging station.The experimental results show that the proposed method has higher accuracy in load estimation of electric vehicle charging stations,better allocation of energy storage capacity,higher operational efficiency,and reliable configuration results.

electric vehiclesoptimizing the configuration of energy storage in charging stationsimprove the algorithm for inva-ding weedsconstraintsglobal optimal solution

杨怀栋、刘杰、李勋、黄鹏、林家豪

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中国南方电网有限责任公司,广州 510623

南方电网电动汽车服务有限公司,深圳 518100

电动汽车 充电站储能优化配置 改进入侵杂草算法 约束条件 全局最优解

南方电网公司技术研究项目

0000002023030301CY00002\3800152022030103JS00006

2024

10.14016/j.cnki.1001-9227.2024.06.033

自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子：0.327
ISSN：1001-9227
年,卷(期)：2024.(6)