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Multi-objective optimization of battery swapping station to power up mobile and stationary loads

Author

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  • Gull, Muhammad Shuzub
  • Khalid, Muhammad
  • Arshad, Naveed

Abstract

The increasing emphasis on clean emission-free transportation has stressed upon the high adoption and penetration of electric vehicles worldwide. However, challenges like range anxiety and long charging time hinder the widespread acceptance. Among various solution the usage of battery swapping station seems more promising as it provide quick battery refueling within a very short time period. The battery swapping station’s progress is limited due to the associated investment and operational cost which needs to be addressed to ensure the global acceptance. In this paper, an optimal battery swapping station operation is proposed based on a multi-objective optimization which combines the generation mix of grid, solar PV, and biogas generation along with the battery arrival using mixed integer programming and orderly charging of discharged batteries to allow the swapping station to operate in battery-to-grid mode using time-dependent dynamic programming. The former reduced the cost of charging while the later increases the swapping station revenue. The combined multi-objective optimization increases the daily net profit by almost 20 times as compared to the base case and by 8% in the optimal operation when the batteries are allowed to be discharged in battery-to-grid mode. The results show that the proposed strategy has potential to significantly boost the daily net profit of the swapping station by increasing revenue and cut cost and can contribute towards the acceptance of swapping station in the current EV market.

Suggested Citation

  • Gull, Muhammad Shuzub & Khalid, Muhammad & Arshad, Naveed, 2024. "Multi-objective optimization of battery swapping station to power up mobile and stationary loads," Applied Energy, Elsevier, vol. 374(C).
    • Handle: RePEc:eee:appene:v:374:y:2024:i:c:s0306261924014478
    DOI: 10.1016/j.apenergy.2024.124064
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    References listed on IDEAS

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    3. Qi, Qi & Zhang, Deying & Hu, Xiang & Li, Xiao & Qi, Bing, 2025. "An optimal dispatch strategy for 5G base stations equipped with battery swapping cabinets," Applied Energy, Elsevier, vol. 392(C).
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    5. Farias, Hericles Eduardo Oliveira & Sepulveda Rangel, Camilo Alberto & Ziquinatti Franciscatto, Bernardo & Klein, Henrique & Silva Neves, Luciane & Gomes, Victor, 2025. "Combined real-time and scheduling methodology for operation of battery swapping stations considering energy flexibility and grid support," Applied Energy, Elsevier, vol. 397(C).
    6. Roudbari, Negin & Firouzjah, Khalil Gorgani & Ghasemi, Jamal, 2025. "Scenario-based sizing and siting of battery swapping stations for electric buses using realistic demand modeling on distribution network," Energy, Elsevier, vol. 341(C).
    7. Maria Grazia Marchesano & Valentina Popolo & Anastasiia Rozhok & Gianluca Cavalaglio, 2024. "Performance Evaluation of Battery Swapping Stations for EVs: A Multi-Method Simulation Approach," Energies, MDPI, vol. 17(23), pages 1-25, November.
    8. Yu Feng & Xiaochun Lu & Xiaohui Huang & Jie Ma, 2025. "Real-Time Electric Taxi Guidance for Battery Swapping Stations Under Dynamic Demand," Energies, MDPI, vol. 18(9), pages 1-16, April.
    9. Bendaouia, Ahmed & Wang, Fenfen & Ouifak, Hafsaa & Li, Jianzhi, 2026. "Digital twin for battery energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PC).
    10. Chen, Jiawen & Zou, Yuan & Zhang, Jun & Zhang, Xudong & Du, Guodong & Meng, Yihao, 2026. "Optimal energy management at solar-integrated hubs for e-taxis with battery swapping and fast charging under power network constraints," Applied Energy, Elsevier, vol. 402(PB).
    11. Du, Pengcheng & Jiang, Meihui & Yang, Bowen & Chen, Baian & Zhu, Hongyu & Mengke, Qilao & Du, Yu & Kong, Fannie & Liu, Tianhao & Huang, Chao & Zhao, Haisen & Goh, Hui Hwang & Zhang, Dongdong, 2025. "Two-layer decomposition-fused hybrid deep learning enables data-driven electricity demand forecasting for battery swapping station," Energy, Elsevier, vol. 332(C).

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