Study on orderly charging of electric vehicles considering participating in grid ancillary services

陈黎军; 宋远军; 王 坤; 汪映辉

doi:10.3969/j.issn.1009-1831.2022.01.007

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Study on orderly charging of electric vehicles considering participating in grid ancillary services

更新时间：2026-03-05

- Study on orderly charging of electric vehicles considering participating in grid ancillary services
- Vol. 24, Issue 1, (2022)
- 作者机构：
  
  1. 国网江苏省电力有限公司,南京,210000
  2. 国网江苏电动汽车服务有限公司,南京,210000
  3. 国电南瑞科技股份有限公司南京,210023
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2022.01.007
  CLC：
- Published：2022
- 稿件说明：
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陈黎军, 宋远军, 王坤, et al. Study on orderly charging of electric vehicles considering participating in grid ancillary services[J]. 2022, 24(1).
DOI：

陈黎军, 宋远军, 王坤, et al. Study on orderly charging of electric vehicles considering participating in grid ancillary services[J]. 2022, 24(1). DOI： 10.3969/j.issn.1009-1831.2022.01.007.

摘要

分析电动汽车充电对电网产生的影响，主要研究对电网负荷平衡的影响。对电动汽车充电负荷建模，分析其用户出行等的时间概率分布，通过蒙特卡罗模拟法对电动汽车充电负荷需求进行计算，研究3 000辆电动汽车全天的充电需求时间分布。建立含光伏发电系统的区域供电系统优化模型，同时以动态电价为激励引导电动汽车进行有序充电，以参与电网辅助服务。以联络线交换功率波动乘积最小和充电成本最低为目标，并以其加权后的函数作为目标函数，结合4个约束条件，通过遗传算法求解模型，得到符合目标函数的最优充电方案。最终通过算例验证该模型能够实现平移负荷、削峰填谷的作用。

Abstract

The impact of electric vehicles to power grid whencharging is analyzed

the main research is about the influence to the balance of power grid load. Then

the electric vehicle chargingload is modeled

and time probability distribution of users’trip isanalyzed

The demand for electric vehicle charging load is calculated by Monte Carlo simulation method

in order to study throughout the time distribution of 3 000 electric vehicles’charging demand

The optimization model of regional power supply system including photovoltaic power generation system is established. Meanwhile

dynamic electricity price is used as incentive to guide electric vehi-cles to carry out orderly charging

so as to participate in power gridancillary services. With the minimum power fluctuation product and the lowest charging cost

the weighted function is taken as the objective function

combined with the four constraints

the geneticalgorithm is used to solve the model

and the optimal chargingscheme is obtained. Finally

an example is given to verify that the model can realize the function of shifting load

cutting peak and filling valley.

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