Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties

LI Jinpeng; FENG Hua; CHEN Xiaogang; ZHANG Hanbing; ZHAN Zhenbin; XU Yinliang

doi:10.7500/AEPS20230830009

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Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties

Special Topic on Key Technologies for Intelligent and Friendly Interaction Between Large-scale Electric Vehicles and Power Grid | 更新时间：2025-06-16

- Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties
- Automation of Electric Power Systems Vol. 48, Issue 7, Pages: 138-146(2024)
- 作者机构：
  
  1.清华大学深圳国际研究生院，广东省深圳市 518000
  2.国网浙江省电力有限公司丽水供电公司，浙江省丽水市 323000
  3.国网浙江省电力有限公司，浙江省杭州市 310027
  4.国网浙江省电力有限公司电力科学研究院，浙江省杭州市 310014
- 作者简介：
- 基金信息：
  
  State Grid Corporation of China(5100-202219501A-3-0-SF)
- DOI：10.7500/AEPS20230830009
  CLC：
- Received：30 August 2023，
  
  Revised：2023-11-22，
  
  Published Online：23 February 2024，
  
  Published：10 April 2024
- 稿件说明：
移动端阅览
李金鹏,冯华,陈晓刚等.计及多重不确定性的规模化电动汽车接入配电网调度方法[J].电力系统自动化,2024,48(7):138-146.

LI Jinpeng,FENG Hua,CHEN Xiaogang,et al.Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties[J].Automation of Electric Power Systems,2024,48(7):138-146.
李金鹏,冯华,陈晓刚等.计及多重不确定性的规模化电动汽车接入配电网调度方法[J].电力系统自动化,2024,48(7):138-146. DOI： 10.7500/AEPS20230830009.

LI Jinpeng,FENG Hua,CHEN Xiaogang,et al.Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties[J].Automation of Electric Power Systems,2024,48(7):138-146. DOI： 10.7500/AEPS20230830009.

摘要

规模日益增长的电动汽车和可再生能源带来的不确定性给配电网的安全运营带来了严峻挑战。为综合考虑多重不确定性、平衡运营成本与系统可靠性，首先，提出一种基于分布鲁棒联合机会约束的电动汽车-配电网充放电调度模型。该模型将节点电压、支路功率、备用需求等通过联合机会约束建模，可以直观地管理系统整体的可靠性。然后，为求解该模型，基于最优Bonferroni近似方法将联合机会约束问题转化为混合整数二次规划模型，其中，风险等级也被视为决策变量。随后，在不同电力系统上验证了所提模型的有效性和可扩展性。结果表明，所提模型克服了经典的随机优化和鲁棒优化存在的问题，能够有效平衡成本和可靠性，计算效率高、可扩展性好，较Bonferroni近似方法降低约6.5%的成本。

Abstract

The escalating scale of electric vehicles (EVs) and renewable energy introduces uncertainties

posing severe challenges to the safe operation of distribution networks. In order to comprehensively consider multiple uncertainties and balance the operation cost with the system reliability

firstly

an EV-distribution network charging and discharging dispatching model based on the distributionally robust joint chance constrainted model is proposed. This model effectively manages the overall system reliability by jointly constraining nodal voltages

branch power

and reserve demand. Then

to solve the model

the joint chance constraint problem is transformed into a mixed-integer quadratic programming model based on the optimized Bonferroni approximation method. Notably

the risk level is also treated as a decision variable. Subsequently

the effectiveness and scalability of the proposed model are verified across various power systems. The results demonstrate that the proposed model overcomes the problems of classical stochastic and robust optimization

effectively balancing cost and reliability with high computational efficiency and good scalability. The model achieves approximately a 6.5% cost reduction compared to the Bonferroni approximation method.

关键词

Keywords

references

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