基于电动汽车有序充电的光储充电站双层优化配置

黄占涛; 周霞; 张腾飞

doi:10.16516/j.ceec.2025-221

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 >

基于电动汽车有序充电的光储充电站双层优化配置

新能源发电与电网支撑 | 更新时间：2026-10-14

- 基于电动汽车有序充电的光储充电站双层优化配置
- Dual-Layer Optimized Configuration of Photovoltaic Storage Charging Station Based on Orderly Charging of Electric Vehicles
- 南方能源建设 2026年13卷第4期页码：154-167
- 作者机构：
  
  南京邮电大学自动化学院、人工智能学院,江苏,南京,210023
- 作者简介：
  
  黄占涛，1999-，男，硕士，从事电力系统规划与优化运行研究工作（e-mail）2812321511@qq.com
  周霞，（e-mail）zhouxia@njupt.edu.cn
  张腾飞，1980-，男，教授，博士，从事智能配电网与配电物联网技术研究工作（e-mail）zhangtf@njupt.edu.cn
- 基金信息：
  
  国家自然科学基金委员会面上项目“基于稳定态势推演的新型电力系统运行方式知识发现与应用研究”（52377085）
- DOI：10.16516/j.ceec.2025-221
  中图分类号： TM715;TM73
- 纸质出版：2026
- 稿件说明：
移动端阅览
黄占涛, 周霞, 张腾飞. 基于电动汽车有序充电的光储充电站双层优化配置[J]. 南方能源建设, 2026, 13(4): 154-167.

.
黄占涛, 周霞, 张腾飞. 基于电动汽车有序充电的光储充电站双层优化配置[J]. 南方能源建设, 2026, 13(4): 154-167. DOI： 10.16516/j.ceec.2025-221.

. DOI： 10.16516/j.ceec.2025-221.

摘要

目的

“双碳”背景下，高比例光伏与电动汽车的大量接入会对电网造成冲击，构建清洁、高效、稳定的光储充电站是实现绿色低碳发展的必然选择。针对光储充电站的配置优化问题，提出了一种基于电动汽车有序充电的光储充电站双层优化配置方法。

方法

首先，基于生成式对抗网络和改进K-means++算法构建典型光伏出力场景库，并结合LSTM-Transformer混合模型对电动汽车充电负荷进行预测，通过分时电价机制引导有序充电，生成优化充电负荷曲线。其次，建立了光储充电站规划-运行双层优化模型，外层以全生命周期成本最小化为目标进行容量配置，内层基于运行经济性与可靠性目标制定运营策略，通过双向参数传递实现规划与运行的动态耦合。最后，采用改进的灰狼优化算法对模型进行求解，获得最优的光储充电站配置方案。

结果

算例分析表明，提出的光储充电站配置策略实现了经济效益最优，有效改善了电网电压质量和稳定性，提高配电网运行水平。

结论

研究结果可为提高配电网运行水平提供参考。

Abstract

Objective

In the context of the "dual carbon" goals

a high proportion of photovoltaic systems and electric vehicles can significantly impact the power grid. Building clean

efficient

and stable photovoltaic storage charging stations is essential for achieving green and low-carbon development. To address the optimization of photovoltaic storage charging station configurations

a two-layer optimization method based on orderly EV charging has been proposed.

Method

his method involves constructing a typical photovoltaic output scenario library using generative adversarial networks and an improved K-means++ algorithm

and predicting EV charging loads with a LSTM-Transformer hybrid model. Time-of-use pricing mechanisms are used to guide orderly charging to optimize the charging load curve. Secondly

a dual-layer optimization model for the planning and operation of photovoltaic storage charging stations is established. The outer layer aims to minimize the total lifecycle cost through capacity configuration

while the inner layer formulates operational strategies based on economic efficiency and reliability. This dynamic coupling between planning and operation is achieved through bidirectional parameter exchange. Finally

an improved grey wolf optimization algorithm is used to solve the model

resulting in the optimal configuration of photovoltaic storage charging stations.

Result

Case studies show that the proposed configuration strategy achieves optimal economic benefits

effectively improves the voltage quality and stability of the power grid

and enhances the operational level of the distribution network.

Conclusion

The research results can provide reference for improving the operation level of the distribution network.

关键词

Keywords

references

CAI M L, FAN R X, HE G D, et al. Source-load-storage coordinated scheduling for active distribution network based on aggregation of electric vehicles with time pattern [J]. Smart power, 2025, 53(1): 54-61. DOI: 10.20204/j.sp.2025.01008.

YU X Y, JI Z S, JI L, et al. Analysis on carbon emission reduction potential of electric vehicles in china under goal of carbon neutrality and carbon peaking [J]. Smart power, 2024, 52(2): 25-31,39. DOI: 10.3969/j.issn.1673-7598.2024.02.004.

LI G J J, YANG J, ZHU X, et al. Real-time energy sharing mechanism for charging stations considering user response characteristics of electric vehicles [J]. Automation of electric power systems, 2022, 46(12): 56-66. DOI: 10.7500/AEPS20211122002.

WANG H X, YUAN J H, CHEN Z, et al. Review and prospect of key techniques for vehicle-station-network integrated operation in smart city [J]. Transactions of China electrotechnical society, 2022, 37(1): 112-132. DOI: 10.19595/j.cnki.1000-6753.tces.211285.

TANG S J, LUO Y T, ZHANG X L, et al. Discussion on problems and development paths of the domestic new energy vehicles charging market [J]. Petroleum and new energy, 2024, 36(5): 10-16,27. DOI: 10.3969/j.issn.2097-0021.2024.05.002.

SANG B Y, YANG B, TAO Y B, et al. An energy storage configuration optimization method considering power probability distribution characteristics of renewable energy [J]. Renewable energy resources, 2024, 42(4): 561-568. DOI: 10.3969/j.issn.1671-5292.2024.04.019.

WANG L Q, WANG Q. Research on participation of wind-solar-storage system in power grid frequency regulation and consumption technology [J]. Inner Mongolia electric power, 2024, 42(1): 9-14. DOI: 10.19929/j.cnki.nmgdljs.2024.0002.

ÇIÇEK A, ŞENGÖR İ, GÜNER S, et al. Integrated rail system and EV parking lot operation with regenerative braking energy, energy storage system and PV availability [J]. IEEE transactions on smart grid, 2022, 13(4): 3049-3058. DOI: 10.1109/tsg.2022.3163343.

WANG S X, ZHANG S T, WANG K, et al. Multi-objective optimal operation of distributed energy storage considering user demand response under time-of-use price [J]. Electric power automation equipment, 2020, 40(1): 125-132. DOI: 10.16081/j.epae.201911029.

HU D H, GUO L, LIU Y X, et al. Stochastic/robust hybrid optimal dispatching of distribution networks considering fast charging stations with photovoltaic and energy storage [J]. Power system technology, 2021, 45(2): 507-517. DOI: 10.13335/j.1000-3673.pst.2020.0838.

ZHANG J, CAI S T, YANG T, et al. Coordinated planning method of charging infrastructure and distribution grid taking into account mobile energy storage vehicles [J]. Proceedings of the CSEE, 2025, 45(11): 4216-4230. DOI: 10.13334/j.0258-8013.pcsee.240294.

YANG H H, SHI Y, HUANG W T, et al. Optimal capacity configuration method of photovoltaic-battery charging station considering real-time demand side response [J]. Smart power, 2023, 51(7): 51-58. DOI: 10.3969/j.issn.1673-7598.2023.07.008.

YAN Q, TU X F. Demand response of photovoltaic electric vehicle charging stations based on weather-impact risk assessment [J]. Journal of Chongqing University, 2023, 46(4): 37-45. DOI: 10.11835/j.issn.1000-582X.2020.202.

LI S B, ZHU Y C, TAN J D, et al. Optimal method for photovoltaic-storage-charging capacity configuration of microgrid-in-chain on expressways considering load spatio-temporal characteristics [J]. Power system technology, 2025, 49(7): 2768-2778. DOI: 10.13335/j.1000-3673.pst.2024.0764.

CHAUDHARI K, UKIL A, KUMAR K N, et al. Hybrid optimization for economic deployment of ESS in PV-integrated EV charging stations [J]. IEEE transactions on industrial informatics, 2018, 14(1): 106-116. DOI: 10.1109/TII.2017.2713481.

BHATTI A R, SALAM Z, SULTANA B, et al. Optimized sizing of photovoltaic grid-connected electric vehicle charging system using particle swarm optimization [J]. International journal of energy research, 2018, 43(1): 500-522. DOI: 10.1002/er.4287.

BAIK S H, JIN Y G, YOON Y T. Determining equipment capacity of electric vehicle charging station operator for profit maximization [J]. Energies, 2018, 11(9): 2301. DOI: 10.3390/en11092301.

JIANG Y, LYU G Y, JIA D X, et al. Optimal allocation of energy storage capacity for photovoltaic energy storage charging stations considering EV user behavior and photovoltaic uncertainty [J]. Zhejiang electric power, 2024, 43(5): 10-17. DOI: 10.19585/j.zjdl.202405002.

LIU L J, WU T, CHEN X D, et al. Multi-objective optimal allocation of DG and EV charging station based on space-time characteristics and demand response [J]. Electric power automation equipment, 2021, 41(11): 48-56. DOI: 10.16081/j.epae.202109003.

SHI J K, BAO Y, CHEN Z, et al. Robust optimization configuration method of energy storage for charging stations considering charging load uncertainty [J]. Automation of electric power systems, 2021, 45(20): 49-58. DOI: 10.7500/AEPS20210302005.

YANG N, LIANG J Z, DING L, et al. Integrated optical storage charging considering reconstruction expansion and safety efficiency cost [J]. Power system technology, 2023, 47(9): 3557-3567. DOI: 10.13335/j.1000-3673.pst.2022.2416.

WANG X H, KE S W, PAN B C, et al. Optimal configuration method of PV-storage capacity of multi-station integration considering submodule characteristics [J]. Southern power system technology, 2025, 19(1): 106-117. DOI: 10.13648/j.cnki.issn1674-0629.2025.01.011.

CHENG S, LIU Y G, LIU W W, et al. Multi-objective optimization based capacity accommodation of PIS considering its economic construction and low-carbon operation [J]. Electric power engineering technology, 2024, 43(4): 147-155. DOI: 10.12158/j.2096-3203.2024.04.015.

YI J B, HU M, WANG Z Y, et al. Multi-objective optimal configuration strategy for improving operation efficiency of photovoltaic energy storage charging stations [J]. Automation of electric power systems, 2024, 48(14): 100-109. DOI: 10.7500/AEPS20230821005.

ZHENG J F, LI T L, MAO S R, et al. Optimal control strategy of customer-side optical storage system under time-of-use electricity price [J]. Computer measurement control, 2021, 29(7): 106-110,116. DOI: 10.16526/j.cnki.11-4762/tp.2021.07.021.

CHEN T X, XU X Y, YAN Z, et al. Optimal operation based on deep reinforcement learning for energy storage system in photovoltaic-storage charging station [J]. Electric power automation equipment, 2021, 41(10): 90-98. DOI: 10.16081/j.epae.202110037.

DONG H Q, WANG L Y, CAO Y W, et al. Capacity configuration and pricing designing method of PV-storage charging station considering user demand response [J]. Acta energiae solaris sinica, 2021, 42(6): 79-86. DOI: 10.19912/j.0254-0096.tynxb.2020-0537.

LIU Y X, DONG H Q, WANG S Y, et al. An optimization approach considering user utility for the PV-storage charging station planning process [J]. Processes, 2020, 8(1): 83. DOI: 10.3390/pr8010083.

DUAN J H. Bilevel programming optimization model of PV-energy storage integrated charging stations considering photovoltaic operation risk [J]. Electric engineering, 2023(22): 67-72. DOI: 10.19768/j.cnki.dgjs.2023.22.018.

BIAN H H, LI C, TONG Y X. Optimized operation strategy of electric vehicle charging stations in shared energy storage mode on two layers [J]. Electric power engineering technology, 2024, 43(5): 170-180. DOI: 10.12158/j.2096-3203.2024.05.017.

YUAN W T, CHEN L, WANG C B, et al. Bi-level optimal scheduling of power-to-ammonia coupling wind-photovoltaic-thermal integrated energy system based on ammonia energy storage technology [J]. Proceedings of the CSEE, 2023, 43(18): 6992-7002. DOI: 10.13334/j.0258-8013.pcsee.223152.

GENG G F, SUN Y Z, NIU X K. Optimal allocation of shared energy storage on the user side and its impact on carbon emissions [J]. Distribution utilization, 2023, 40(3): 32-39. DOI: 10.19421/j.cnki.1006-6357.2023.03.005.

HU W, YANG S. Dual-tiered optimization configuration model for energy storage considering distribution network vulnerability [J]. Smart power, 2024, 52(6): 1-8. DOI: 10.3969/j.issn.1673-7598.2024.06.002.

HE J, CHEN W Y, QI L J, et al. Research on capacity configuration and operation optimization of photovoltaic-storage charging station in expressway service area [J]. Journal of Wuhan University of Technology (transportation science engineering), 2025, 49(6): 1169-1175. DOI: 10.3963/j.issn.2095-3844.2025.06.001.

ZHANG J Y, FANG B, WANG S L, et al. PV-energy storage coordinated low-carbon optimization considering battery lifetime [J]. Battery bimonthly, 2026, 56(2): 440-446. DOI: 10.19535/j.1001-1579.2026.02.021.

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

基于通道差异响应与动态阈值的WPT-FOD方法

碳电市场耦合机制研究综述：模型分类、联动路径与挑战展望

锂电池储能电站安全风险预警技术及工程应用综述

多元混合储能系统监测与预警技术综述

基于切圆布气的人工硐室壁温抑制技术