A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints
Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capaci...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/16/5/250 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850126115885023232 |
|---|---|
| author | Qingyu Yin Lili Li Jian Zhang Xiaonan Liu Boqiang Ren |
| author_facet | Qingyu Yin Lili Li Jian Zhang Xiaonan Liu Boqiang Ren |
| author_sort | Qingyu Yin |
| collection | DOAJ |
| description | Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions. |
| format | Article |
| id | doaj-art-2605a9fc2707495aaf06bf3453c27a80 |
| institution | OA Journals |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-2605a9fc2707495aaf06bf3453c27a802025-08-20T02:33:59ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-04-0116525010.3390/wevj16050250A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity ConstraintsQingyu Yin0Lili Li1Jian Zhang2Xiaonan Liu3Boqiang Ren4Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610000, ChinaSichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610000, ChinaState Grid Tianjin Electric Power Company, Tianjin 300010, ChinaState Grid Tianjin Electric Power Company, Tianjin 300010, ChinaState Grid Tianjin Electric Power Company, Tianjin 300010, ChinaGrid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions.https://www.mdpi.com/2032-6653/16/5/250ultra-fast charging (UFC)active load management (ALM)battery energy storage system (BESS)grid capacity constraintslevelized cost of electricity (LCOE)internal rate of return (IRR) |
| spellingShingle | Qingyu Yin Lili Li Jian Zhang Xiaonan Liu Boqiang Ren A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints World Electric Vehicle Journal ultra-fast charging (UFC) active load management (ALM) battery energy storage system (BESS) grid capacity constraints levelized cost of electricity (LCOE) internal rate of return (IRR) |
| title | A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints |
| title_full | A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints |
| title_fullStr | A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints |
| title_full_unstemmed | A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints |
| title_short | A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints |
| title_sort | multi scheme comparison framework for ultra fast charging stations with active load management and energy storage under grid capacity constraints |
| topic | ultra-fast charging (UFC) active load management (ALM) battery energy storage system (BESS) grid capacity constraints levelized cost of electricity (LCOE) internal rate of return (IRR) |
| url | https://www.mdpi.com/2032-6653/16/5/250 |
| work_keys_str_mv | AT qingyuyin amultischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT lilili amultischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT jianzhang amultischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT xiaonanliu amultischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT boqiangren amultischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT qingyuyin multischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT lilili multischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT jianzhang multischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT xiaonanliu multischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints AT boqiangren multischemecomparisonframeworkforultrafastchargingstationswithactiveloadmanagementandenergystorageundergridcapacityconstraints |