Optimization strategy for soft open point-containing active distribution networks considering carbon-guided electric vehicle clustering

doi:10.3785/j.issn.1008-973X.2025.09.016

Journal of ZheJiang University (Engineering Science)

2025, Vol. 59

Issue (9): 1920-1930 DOI: 10.3785/j.issn.1008-973X.2025.09.016

Optimization strategy for soft open point-containing active distribution networks considering carbon-guided electric vehicle clustering

Renwu YAN1(

),Jianxiong LIN1,Chenxin YE2,Rong YE3,Peiqiang LI4,Yu KUANG5

1. School of Electrical, Electronics, and Physics, Fujian University of Technology, Fuzhou 350118, China
2. Fuzhou Changle District Power Supply Company of State Grid Co. Ltd, Fuzhou 350200, China
3. Fuzhou Power Supply Company of State Grid Co. Ltd, Fuzhou 350009, China
4. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
5. State Grid Xinyuan Company Zhejiang Panan Pumped Storage Co. Ltd, Jinhua 322304, China

Download:

HTML

PDF(1680KB) HTML
Export: BibTeX | EndNote (RIS)

Abstract

A bi-level optimization strategy for active distribution networks with smart soft open point (SOP) considering carbon-guided electric vehicle (EV) clustering was proposed, in order to improve the consumption of wind-solar new energy and fully exploit the potential of EV clusters in optimal operation of active distribution networks for carbon emission reduction. Firstly, under the premise of EV cluster integration, the active/reactive power outputs of distributed generators and SOPs were coordinated and optimized by the upper layer to minimize system operation costs. Secondly, the lower-layer generalized energy storage optimization model for EV clusters based on Minkowski sums was constructed to minimize charging-discharging costs. A dynamic tariff mechanism based on dynamic carbon emission factor was proposed to guide vehicle-grid energy interaction and achieve win-win benefits for both parties. Finally, simulation verification on the improved IEEE 33-node system showed that the strategy could effectively promote friendly interaction between active distribution network and EV cluster, reducing the risk of system voltage overruns.

Key words： electric vehicle active distribution network soft open point dynamic carbon emission factor dynamic tariff

Received: 25 September 2024 Published: 25 August 2025

CLC:

TM 73

Fund: 国家自然科学基金资助项目(52377097) .

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Renwu YAN
	Jianxiong LIN
	Chenxin YE
	Rong YE
	Peiqiang LI
	Yu KUANG

Cite this article:

Renwu YAN,Jianxiong LIN,Chenxin YE,Rong YE,Peiqiang LI,Yu KUANG. Optimization strategy for soft open point-containing active distribution networks considering carbon-guided electric vehicle clustering. Journal of ZheJiang University (Engineering Science), 2025, 59(9): 1920-1930.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2025.09.016 OR https://www.zjujournals.com/eng/Y2025/V59/I9/1920

考虑碳量引导EV集群的含智能软开关主动配电网优化策略

为了提高风光新能源消纳，充分挖掘电动汽车（EV）集群参与主动配电网优化运行以及降低系统碳排放的潜力，提出考虑碳量引导EV集群的含智能软开关（SOP）主动配电网双层优化策略. 上层在EV集群接入前提下，以系统运行成本最低为目标，协调优化分布式电源以及智能软开关的有功无功出力；以充放电成本最低为目标构建下层基于闵可夫斯基和的EV集群广义储能优化模型，并提出基于动态碳排放因子的动态电价机制引导车网能量交互，实现双方主体利益共赢. 通过改进IEEE 33节点系统进行仿真验证，结果表明，该策略能够有效促进主动配电网与EV集群间的友好互动，减少系统电压越限风险.

关键词： 电动汽车, 主动配电网, 智能软开关, 动态碳排放因子, 动态电价

Fig.1 Minkowski addition

Fig.2 Flowchart for solving bi-level model

Fig.3 Improved IEEE-33 node topology map

Tab.1 Sampling parameters for each EV cluster

Fig.4 Wind power forecast output and base load

Tab.2 Costs in different scenarios

Fig.5 Scheduling plan diagrams for different scenarios

Fig.6 Dynamic electricity prices and dynamic carbon emission factors

Fig.7 EV cluster charging and discharging

Tab.3 Load variation in different scenarios

Fig.8 Load profiles for different scenarios

Tab.4 Cost of components under SOP access

Fig.9 Output power curves of SOP

Tab.5 Voltage offsets in different scenarios

Fig.10 Voltage offsets in different scenarios

Fig.11 solution time under different models


[1]	辛保安, 单葆国, 李琼慧, 等 “双碳” 目标下“能源三要素” 再思考[J]. 中国电机工程学报, 2022, 42 (9): 3117- 3126 XIN Baoan, SHAN Baoguo, LI Qionghui, et al Rethinking of the “three elements of energy” toward carbon peak and carbon neutrality[J]. Proceedings of the CSEE, 2022, 42 (9): 3117- 3126

[2]	JI Z, HUANG X Plug-in electric vehicle charging infrastructure deployment of China towards 2020: policies, methodologies, and challenges[J]. Renewable and Sustainable Energy Reviews, 2018, 90: 710- 727 doi: 10.1016/j.rser.2018.04.011

[3]	裴振坤, 王学梅, 康龙云电动汽车参与电网辅助服务的控制策略综述[J]. 电力系统自动化, 2023, 47 (18): 17- 32 PEI Zhenkun, WANG Xuemei, KANG Longyun Review on control strategies for electric vehicles participating in ancillary services of power grid[J]. Automation of Electric Power Systems, 2023, 47 (18): 17- 32 doi: 10.7500/AEPS20220728005

[4]	KE S, CHEN L, YANG J, et al Vehicle to everything in the power grid (V2eG): a review on the participation of electric vehicles in power grid economic dispatch[J]. Energy Conversion and Economics, 2022, 3 (5): 259- 286 doi: 10.1049/enc2.12070

[5]	程杉, 钟仕凌, 尚冬冬, 等考虑电动汽车时空负荷分布特性的主动配电网动态重构[J]. 电力系统保护与控制, 2022, 50 (17): 1- 13 CHENG Shan, ZHONG Shiling, SHANG Dongdong, et al Dynamic reconfiguration of an active distribution network considering temporal and spatial load distribution characteristics of electric vehicles[J]. Power System Protection and Control, 2022, 50 (17): 1- 13

[6]	林文键, 朱振山, 温步瀛含电动汽车和智能软开关的配电网动态重构[J]. 电力自动化设备, 2022, 42 (10): 202- 209,217 LIN Wenjian, ZHU Zhenshan, WEN Buying Dynamic reconfiguration of distribution network with electric vehicles and soft open point[J]. Electric Power Automation Equipment, 2022, 42 (10): 202- 209,217

[7]	王岩庆, 王骁, 丛若晨, 等考虑配电网运行安全的出行电动汽车充电引导策略[J]. 高电压技术, 2023, 49 (5): 2131- 2139 WANG Yanqing, WANG Xiao, CONG Ruochen, et al Charging guidance strategy of traveling electric vehicle considering the operation safety of distribution network[J]. High Voltage Engineering, 2023, 49 (5): 2131- 2139

[8]	蔡小婷, 杨健维, 廖凯, 等考虑负荷时空均衡和弹性响应的电动汽车快充电价定价策略[J]. 电力自动化设备, 2024, 44 (2): 94- 102 CAI Xiaoting, YANG Jianwei, LIAO Kai, et al Pricing strategy of electric vehicle fast charging price considering space-time equilibrium and elastic response of load[J]. Electric Power Automation Equipment, 2024, 44 (2): 94- 102

[9]	郝丽丽, 王国栋, 王辉, 等考虑电动汽车入网辅助服务的配电网日前调度策略[J]. 电力系统自动化, 2020, 44 (14): 35- 43 HAO Lili, WANG Guodong, WANG Hui, et al Day-ahead scheduling strategy of distribution network considering electric vehicle-to-grid auxiliary service[J]. Automation of Electric Power Systems, 2020, 44 (14): 35- 43

[10]	张良, 孙成龙, 蔡国伟, 等基于PSO算法的电动汽车有序充放电两阶段优化策略[J]. 中国电机工程学报, 2022, 42 (5): 1837- 1852 ZHANG Liang, SUN Chenglong, CAI Guowei, et al Two-stage optimization strategy for coordinated charging and discharging of EVs based on PSO algorithm[J]. Proceedings of the CSEE, 2022, 42 (5): 1837- 1852

[11]	张潇, 栗然, 马涛, 等基于主从博弈和贪心策略的含电动汽车主动配电网优化调度[J]. 电力自动化设备, 2020, 40 (4): 103- 110 ZHANG Xiao, LI Ran, MA Tao, et al Stackelberg game and greedy strategy based optimal dispatch of active distribution network with electric vehicles[J]. Electric Power Automation Equipment, 2020, 40 (4): 103- 110

[12]	王成山, 季节, 冀浩然, 等配电系统智能软开关技术及应用[J]. 电力系统自动化, 2022, 46 (4): 1- 14 WANG Chengshan, JI Jie, JI Haoran, et al Technologies and application of soft open points in distribution networks[J]. Automation of Electric Power Systems, 2022, 46 (4): 1- 14

[13]	HUO Y, LI P, JI H, et al Data-driven adaptive operation of soft open points in active distribution networks[J]. IEEE Transactions on Industrial Informatics, 2021, 17 (12): 8230- 8242 doi: 10.1109/TII.2021.3064370

[14]	熊正勇, 陈天华, 杜磊, 等基于改进灵敏度分析的有源配电网智能软开关优化配置[J]. 电力系统自动化, 2021, 45 (8): 129- 137 XIONG Zhengyong, CHEN Tianhua, DU Lei, et al Optimal allocation of soft open point in active distribution network based on improved sensitivity analysis[J]. Automation of Electric Power Systems, 2021, 45 (8): 129- 137

[15]	王杰, 王维庆, 王海云, 等考虑越限风险的主动配电网中DG、SOP与ESS的两阶段协调规划[J]. 电力系统保护与控制, 2022, 50 (24): 71- 82 WANG Jie, WANG Weiqing, WANG Haiyun, et al Two-stage coordinated planning of DG, SOP and ESS in an active distribution network considering violation risk[J]. Power System Protection and Control, 2022, 50 (24): 71- 82

[16]	章博, 刘晟源, 林振智, 等高比例新能源下考虑需求侧响应和智能软开关的配电网重构[J]. 电力系统自动化, 2021, 45 (8): 86- 94 ZHANG Bo, LIU Shengyuan, LIN Zhenzhi, et al Distribution network reconfiguration with high penetration of renewable energy considering demand response and soft open point[J]. Automation of Electric Power Systems, 2021, 45 (8): 86- 94

[17]	章攀钊, 谢丽蓉, 马瑞真, 等考虑电动汽车集群可调度能力的多主体两阶段低碳优化运行策略[J]. 电网技术, 2022, 46 (12): 4809- 4825 ZHANG Panzhao, XIE Lirong, MA Ruizhen, et al Multi-player two-stage low carbon optimal operation strategy considering electric vehicle cluster schedulability[J]. Power System Technology, 2022, 46 (12): 4809- 4825

[18]	詹祥澎, 杨军, 韩思宁, 等考虑电动汽车可调度潜力的充电站两阶段市场投标策略[J]. 电力系统自动化, 2021, 45 (10): 86- 96 ZHAN Xiangpeng, YANG Jun, HAN Sining, et al Two-stage market bidding strategy of charging station considering schedulable potential capacity of electric vehicle[J]. Automation of Electric Power Systems, 2021, 45 (10): 86- 96

[19]	傅长熠, 杨镜非, 顾家辉基于双层动态时段划分的配电网重构[J]. 电力自动化设备, 2022, 42 (6): 30- 36,52 FU Changyi, YANG Jingfei, GU Jiahui Reconfiguration of distribution network based on bi-level dynamic time division[J]. Electric Power Automation Equipment, 2022, 42 (6): 30- 36,52

[20]	宋泽淏, 冯华, 陈晓刚, 等基于节点碳势的配电网分布式资源低碳调度策略[J]. 高电压技术, 2023, 49 (6): 2320- 2332 SONG Zehao, FENG Hua, CHEN Xiaogang, et al Low-carbon scheduling strategy of distributed energy resources based on node carbon intensity for distribution networks[J]. High Voltage Engineering, 2023, 49 (6): 2320- 2332

[21]	高红均, 刘俊勇, 沈晓东, 等主动配电网最优潮流研究及其应用实例[J]. 中国电机工程学报, 2017, 37 (6): 1634- 1645 GAO Hongjun, LIU Junyong, SHEN Xiaodong, et al Optimal power flow research in active distribution network and its application examples[J]. Proceedings of the CSEE, 2017, 37 (6): 1634- 1645

[22]	葛津铭, 刘志文, 王朝斌, 等考虑需求响应的高比例光伏配电网低碳调度[J]. 电网技术, 2024, 48 (5): 1929- 1937 GE Jinming, LIU Zhiwen, WANG Chaobin, et al Low-carbon dispatching of high proportion photovoltaic distribution network considering demand response[J]. Power System Technology, 2024, 48 (5): 1929- 1937

[23]	米阳, 申杰, 卢长坤, 等考虑含储能的三端智能软开关与需求侧响应的主动配电网有功无功协调优化[J]. 电力系统保护与控制, 2024, 52 (3): 104- 118 MI Yang, SHEN Jie, LU Changkun, et al Active and reactive power coordination optimization of an active distribution network considering a three-terminal soft open point with energy storage and demand response[J]. Power System Protection and Control, 2024, 52 (3): 104- 118

[24]	王成磊, 匡熠, 濮永现, 等基于改进生成对抗网络场景生成的长-短期储能优化配置[J]. 高电压技术, 2024, 50 (3): 1131- 1144 WANG Chenglei, KUANG Yi, PU Yongxian, et al Optimal configuration of long-term and short-term energy storage based on improved generative adversarial network scenarios[J]. High Voltage Engineering, 2024, 50 (3): 1131- 1144

[1]	Didi LIU,Songxiu ZHONG,Yituan LIU,Yanli ZOU,Chaochen TANG. Optimization strategy for smart home energy management through synergistic integration of photovoltaic systems and electric vehicles[J]. Journal of ZheJiang University (Engineering Science), 2025, 59(9): 1902-1910.

[2]	Xi-qun CHEN,Yi-wei QIAN,Dong MO. Collaborative optimization of charging pile quantity and price for electric vehicle charging platform[J]. Journal of ZheJiang University (Engineering Science), 2023, 57(9): 1785-1793.

[3]	Kai DU,Guo-rong ZHU,Jiang-hua LU,Mu-ye PANG. Metal object detection method in wireless electric vehicle charging system[J]. Journal of ZheJiang University (Engineering Science), 2022, 56(1): 56-62.

[4]	Fei JU,Wei-chao ZHUANG,Liang-mo WANG,Jing-xing LIU,Qun WANG. Velocity planning strategy for economic cruise of hybrid electric vehicles[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(8): 1538-1547.

[5]	Jia-jia WANG,Ying-feng CAI,Long CHEN,Shao-hua WANG,De-hua SHI. Coordinated control of hybrid electric vehicle based on extended state observer estimation[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(7): 1225-1233.

[6]	Xue XIA,Zhen ZHAO,Jin-jie ZHANG,Liang TANG. Mechanical integrity of cylindrical automotive lithium-ion batteries and modules[J]. Journal of ZheJiang University (Engineering Science), 2021, 55(11): 2134-2141.

[7]	Dong-dong JIANG,Dao-fei LI,Xiao-li YU. Model predictive control energy management based ondriver demand torque prediction[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(7): 1325-1334.

[8]	Xia SHANG,Mei-jia WANG,Liu-xiao XU,Li-hui ZHANG. Configuration optimization of electric vehicle charging facilities in urban areas[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(6): 1210-1217.

[9]	CHU Liang, LI Tian-jiao, SUN Cheng-wei. Research on adaptive cruise control strategy for electric vehicle based on optimization of regenerative braking[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(8): 1596-1602.

[10]	SUN Yue, JIA Xin, TANG Chun-sen. Pick-up position detection for WPT-EV based on three-coil synthesis algorithm[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(5): 984-991.

[11]	PAN Ning, YU Liang yao, ZHANG Lei, SONG Jian, ZHANG Yong hui. Anti-lock braking control in coordinated braking system considering braking comfort[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(1): 9-16.

[12]	YE Li ya, WANG Zhen, WEN Fu shuan, YANG Jun, JIANG Dao zhuo. Economic benefit evaluation of V2G aggregator for frequency regulation[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(9): 1831-1840.

[13]	MA Hao jun, ZHU Shao peng, YU Xiao li, XU Yin chuan, LIN Ding. Electronic differential control considering rolling movement for electric vehicles[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(3): 566-573.

[14]	JIANG Dong dong, LI Dao fei, YU Xiao li. Energy management strategy of dual drive hybrid electric vehicle[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(12): 2245-2253.

[15]	IU Bin-bin, ZHU Shao-peng, MA Hao-jun, FANG Guang-ming, YING Zhen-you, NING Xiao-bin. Design on simulation and test platform of electric vehicle’s drive control system Q [J]. Journal of ZheJiang University (Engineering Science), 2015, 49(6): 1154-1159.

Viewed

Full text

Abstract

Cited

Shared

Discussed