摘要
电动汽车的发展对于推动双碳目标实现具有重要作用,但是大规模的电动汽车负荷接入电网后,会影响电网的安全运行,光储充一体化系统可以利用光伏系统、充电站和储能系统平衡电动汽车充电负荷引起的波动,故容量优化配置方法的选取对光储充一体化系统的建设与发展至关重要。首先对光储充一体化系统的组成以及光储充一体化充电站发展现状作了简要的概述,列举国内典型的光储充一体化系统示范项目的分布情况。然后分析了电动汽车充电负荷影响因素及基于蒙特卡罗法的电动汽车负荷预测方法。最后比较了几种典型的优化算法应用于系统容量配置的优缺点,以期为科学合理地配置光储充一体化系统的容量提供借鉴。
The development of electric vehicles plays an important role in promoting the double carbon goal.However,the large-scale electric vehicle load connected to the power grid will affect the safe operation of the power grid.The PV-energy storage-charging integrated system is a green and intelligent charging mode for the reason that it can use photovoltaic system.Therefore,how to configure the capacity of the photovoltaic and energy storage system,And the selection of capacity optimization method is very important for the construction and development of optical storage and charging integrated system.Firstly,a brief overview of the composition of the integrated optical storage and charging system and the development status of the integrated optical storage and charging charging station is giver,and the distribution of typical domestic integrated optical storage and charging system demonstration projects is listed.Then the influencing factors of electric vehicle charging load and the electric vehicle load forecasting method based on Monte Carlo method is analyzed.Finally,the advantages and disadvantages of several typical optimization algorithms applied to the system capacity configuration are compared,in order to provide reference for the scientific and reasonable configuration of the capacity of the integrated optical storage and charging system.
作者
李建林
许璐
马凌怡
LI Jianlin;XU Lu;MA Lingyi(Energy Storage Technology Engineering Research Center(North China University of Technology),Bejing 100144,China)
出处
《电气应用》
2022年第9期71-77,共7页
Electrotechnical Application
基金
大学生创新创业课题“兆瓦级储能三电平变流器仿真建模及控制策略研究”(108051360022XN296)
国家电投集团科学技术研究院科技项目“电源侧储能创新课题研究”(126005JX0120220023)研究成果。
关键词
光储充一体化系统
电动汽车
蒙特卡罗法
容量配置
多目标优化算法
PV-energy storage-charging integrated system
electric vehicle
Monte Carlo method
capacity configuration
multi-objective optimization algorithm
