Practice in Differentiated Charging Facility Planning for Urban Areas Based on Simulated Trip Chains of Electric Vehicles

MA Zechao; LIU Xiaoming; WANG Weiqiang; XIA Hanqing; YANG Shangjiang; YOU Xiancheng

doi:10.7500/AEPS20240930006

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Practice in Differentiated Charging Facility Planning for Urban Areas Based on Simulated Trip Chains of Electric Vehicles

Basic Research | 更新时间：2026-09-01

- Practice in Differentiated Charging Facility Planning for Urban Areas Based on Simulated Trip Chains of Electric Vehicles
- Automation of Electric Power Systems Vol. 50, Issue 17, Pages: 176-188(2026)
- 作者机构：
  
  1.北方工业大学电气与控制工程学院，北京市 100144
  2.南京航空航天大学民航学院，江苏省南京市 211106
  3.大亚湾核电运营管理有限责任公司，广东省深圳市 518124
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2018YFB1601003)
- DOI：10.7500/AEPS20240930006
  CLC：
- Received：30 September 2024，
  
  Revised：2025-02-17，
  
  Online First：14 January 2026，
  
  Published：10 September 2026
- 稿件说明：
移动端阅览
马泽超,刘小明,王伟强等.基于电动汽车仿真行程链的城市差异化充电设施规划实践[J].电力系统自动化,2026,50(17):176-188.

MA Zechao,LIU Xiaoming,WANG Weiqiang,et al.Practice in Differentiated Charging Facility Planning for Urban Areas Based on Simulated Trip Chains of Electric Vehicles[J].Automation of Electric Power Systems,2026,50(17):176-188.
马泽超,刘小明,王伟强等.基于电动汽车仿真行程链的城市差异化充电设施规划实践[J].电力系统自动化,2026,50(17):176-188. DOI： 10.7500/AEPS20240930006.

MA Zechao,LIU Xiaoming,WANG Weiqiang,et al.Practice in Differentiated Charging Facility Planning for Urban Areas Based on Simulated Trip Chains of Electric Vehicles[J].Automation of Electric Power Systems,2026,50(17):176-188. DOI： 10.7500/AEPS20240930006.

摘要

针对城市电动汽车充电设施发展规模差异扩大的问题，提出了一种基于仿真行程链的差异化充电设施规划模型。以北京市为例，整合车辆运行、建筑环境和充电设施等多源数据，从时间、空间和能量维度提取用户特征，基于高斯混合聚类和谱聚类的两步聚类模型构建具有差异化特征的用户群组。通过大规模行程链构建潜在充电需求分布网络，采用社区发现算法将其划分为13个具有差异特征的子区。各子区在充电设施规模、分时价格、土地功能占比和充电需求热点分布等方面存在差异。针对这些差异，规划模型在不同区位采用独立的建设约束，并将地理加权回归得到的属性影响因子作为目标函数权重，实现差异化考量。优化方案使充电需求过饱和地区的用电量降低了3.35%，显著减少了碳排放，且新建充电设施在高峰时段的利用率优于旧设施。

Abstract

To address the growing disparity in the development scale of urban electric vehicle charging facilities

this paper proposes a differentiated charging facility planning model based on simulated trip chains. Taking Beijing municipality as an example

multi-source data such as vehicle operation

built environment

and charging facilities are integrated to extract user characteristics from time

space

and energy dimensions. And user groups with differentiated characteristics are constructed based on the two-step clustering model of Gaussian mixture clustering and spectral clustering. The potential charging demand distribution network is constructed from a large-scale trip chain and divided into 13 sub-areas with various characteristics by using the community detection algorithm. These sub-areas show differences in charging infrastructure scale

time-of-use pricing

land-use composition

and charging demand hotspot distribution. In view of these differences

the planning model adopts independent construction constraints for various sub-areas and takes the attribute influence factors derived from geographically weighted regression as the weights of the objective function to realize differentiation considerations. The optimized scheme reduces electricity consumption by 3.35% in the areas with oversaturated charging demand

significantly reducing carbon emissions

and the utilization rate of newly constructed charging facilities during peak hours is better than that of old facilities.

关键词

Keywords

references

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