Application of Mobile Soft Open Points to Enhance Hosting Capacity of EV Charging Stations

The rapid growth of electric vehicle (EV) charging demand poses significant challenges to distribution networks (DNs), particularly during public holidays when concentrated peaks occur near scenic areas and urban transport hubs. These sudden surges can strain transformer capacity and compromise supply reliability. Fixed soft open points (SOPs) are costly and underutilized, limiting their effectiveness in DNs with multiple transformers and asynchronous peak loads. To address this, from the perspective of power supply companies, this study proposes a mobile soft open point (MSOP)-based approach to enhance the hosting capacity of EV charging stations. The method pre-installs a limited number of fast-access interfaces (FAIs) at candidate transformers and integrates a semi-rolling horizon optimization framework to gradually expand interface availability while scheduling MSOPs daily. An automatic peak period identification algorithm ensures optimization focuses on critical load periods. Case studies on a multi-feeder distribution system coupled with a realistic traffic network demonstrate that the proposed method effectively balances heterogeneous peak loads, matches limited interfaces with MSOPs, and enhances system-level hosting capacity. Compared with fixed SOP deployment, the strategy improves hosting capacity during peak periods while reducing construction costs. The results indicate that MSOPs provide a practical, flexible, and economically efficient solution for power supply companies to manage concentrated holiday charging surges in DNs.

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Publication Details

Journal
Energies
Published
2025-10-31
DOI
https://doi.org/10.3390/en18215758
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Application of Mobile Soft Open Points to Enhance Hosting Capacity of EV Charging Stations

Guowei Guo, Qi Ye, David W. Lin, Jiaxin Peng et al.
1 citations
Energies
Electric Vehicles and Infrastructure
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article

Application of Mobile Soft Open Points to Enhance Hosting Capacity of EV Charging Stations

Guowei Guo, Qi Ye, David W. Lin, Jiaxin Peng, Qiaoling Dai, Zhenhua Chen, Chutao Zheng
article en
1 citations

Abstract

The rapid growth of electric vehicle (EV) charging demand poses significant challenges to distribution networks (DNs), particularly during public holidays when concentrated peaks occur near scenic areas and urban transport hubs. These sudden surges can strain transformer capacity and compromise supply reliability. Fixed soft open points (SOPs) are costly and underutilized, limiting their effectiveness in DNs with multiple transformers and asynchronous peak loads. To address this, from the perspective of power supply companies, this study proposes a mobile soft open point (MSOP)-based approach to enhance the hosting capacity of EV charging stations. The method pre-installs a limited number of fast-access interfaces (FAIs) at candidate transformers and integrates a semi-rolling horizon optimization framework to gradually expand interface availability while scheduling MSOPs daily. An automatic peak period identification algorithm ensures optimization focuses on critical load periods. Case studies on a multi-feeder distribution system coupled with a realistic traffic network demonstrate that the proposed method effectively balances heterogeneous peak loads, matches limited interfaces with MSOPs, and enhances system-level hosting capacity. Compared with fixed SOP deployment, the strategy improves hosting capacity during peak periods while reducing construction costs. The results indicate that MSOPs provide a practical, flexible, and economically efficient solution for power supply companies to manage concentrated holiday charging surges in DNs.

EnergiesVol. 18(21)
China Southern Power Grid (China) (CN), South China University of Technology (CN)
South China University of Technology, China Southern Power Grid
Openalex Percentile: Top 22%
Electric Vehicles and Infrastructure
0.73
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