基于节点差异化充电价格引导的充电负荷时空优化策略

张 良; 龙彦良; 戚佳金; 王殿彬; 黄南天; 江丽洋

doi:10.19783/j.cnki.pspc.256007

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

基于节点差异化充电价格引导的充电负荷时空优化策略

电动汽车充换电与驱动系统专题 | 更新时间：2026-07-19

- 基于节点差异化充电价格引导的充电负荷时空优化策略
- A spatiotemporal optimization strategy for electric vehicle charging loads guided by node-differentiated charging prices
- 电力系统保护与控制 2026年54卷第14期
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.19783/j.cnki.pspc.256007
  中图分类号：
- 纸质出版：2026
- 稿件说明：
移动端阅览
张良, 龙彦良, 戚佳金, 等. 基于节点差异化充电价格引导的充电负荷时空优化策略[J]. 电力系统保护与控制, 2026,54(14).

ZHANG Liang, LONG Yanliang, QI Jiajin, et al. A spatiotemporal optimization strategy for electric vehicle charging loads guided by node-differentiated charging prices[J]. Power System Protection and Control, 2026, 54(14).
张良, 龙彦良, 戚佳金, 等. 基于节点差异化充电价格引导的充电负荷时空优化策略[J]. 电力系统保护与控制, 2026,54(14). DOI： 10.19783/j.cnki.pspc.256007.

ZHANG Liang, LONG Yanliang, QI Jiajin, et al. A spatiotemporal optimization strategy for electric vehicle charging loads guided by node-differentiated charging prices[J]. Power System Protection and Control, 2026, 54(14). DOI： 10.19783/j.cnki.pspc.256007.

摘要

针对大规模电动汽车接入配电网带来的负荷分配不均与电能质量下降问题，提出一种融合多因素用户响应特性与电网运行状态自适应调节的节点差异化充电价格机制及充电负荷空间优化策略。首先，该策略综合考虑充电站节点的安全性、经济性与可用性指标，构成差异化充电价格制定的核心依据。然后，依据配电网实时运行状态动态调整各指标权重，进而制定节点电价机制，引导电动汽车用户选择最优充电站点，实现负荷在空间上的合理再分配。最后，在IEEE33节点与69节点系统中进行仿真验证。结果表明，所提方法有助于提升充电站运行效率，缓解电网负荷压力，并为电动汽车与电网的协同发展提供技术支撑。

Abstract

To address the problems of uneven load distribution and deteriorated power quality caused by the large-scale electric vehicle integration into distribution networks

a node-differentiated charging pricing mechanism and a charging load spatial optimization strategy integrating multi-factor user response characteristics and adaptive adjustment of grid operation states are proposed. First

the proposed strategy comprehensively considers the safety

economy

and availability of charging station nodes

forming the core basis for differentiated charging price formulation. Then

it dynamically adjusts the weights of these indicators according to the real-time operation states of the distribution network

thereby formulating a node electricity pricing mechanism to guide electric vehicle users to select optimal charging stations and achieve a more balanced spatial load redistribution. Finally

simulation verification is conducted on the IEEE 33-bus and 69-bus systems. The results show that the proposed method effectively improves charging station operation efficiency

alleviates grid load pressure

and provides technical support for the coordinated development of electric vehicles and power grids.

关键词

Keywords

references

XU Biao, ZHANG Guiyuan, LI Ke, et al. Reactive power optimization of a distribution network with high-penetration of wind and solar renewable energy and electric vehicles[J]. Protection and Control of Modern Power Systems, 2022, 7(4): 1-13.

HU Wei, WANG Shuo, DU Puliang. An optimized distribution model for energy system in virtual power plants integrating electric vehicles based on TD3 and DQN[J]. Protection and Control of Modern Power Systems, 2025, 10(6): 31-48.

ZHAO Zhonghao, LEE C K M. Dynamic pricing for EV charging stations: a deep reinforcement learning approach[J]. IEEE Transactions on Transportation Electrification, 2022, 8(2): 2456-2468.

LAI Shuying, QIU Jing, TAO Yuechuan, et al. Pricing for electric vehicle charging stations based on the responsiveness of demand[J]. IEEE Transactions on Smart Grid, 2023, 14(1): 530-544.

KUANG H, ZHANG X, QU H, et al. Unraveling the effect of electricity price on electric vehicle charging behavior: a case study in Shenzhen, China[J]. Sustainable Cities and Society, 2024, 115.

CUI Y, HU Z, DUAN X. Optimal pricing of public electric vehicle charging stations considering operations of coupled transportation and power systems[J]. IEEE Transactions on Smart Grid, 2021, 12(4): 3278-3288.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于实时监测数据的海上风电分钟级超短期多步功率预测模型

考虑温度影响的电动汽车集群市场化双型需求响应运营策略

基于主动探测式的双端弱馈交流系统模型识别纵联保护

考虑转供率和容载比的主动配电网供电能力提升研究

基于元学习与改进 Transformer 的 N-k 小样本暂态稳定事故筛选方法