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Multi-objective optimization framework for strategic placement of electric vehicle charging stations and shunt capacitors in a distribution network considering traffic flow

Author

Listed:
  • Kumar, B.Vinod
  • M.A., Aneesa Farhan

Abstract

This study aims to develop a comprehensive multi-objective planning framework for the optimal placement of Electric Vehicle Charging Stations (EVCS) and Shunt Capacitors (SCs) in the distribution network (DN) while accounting for transportation network (TN) constraints. The integration of EVCS into DN, though essential for promoting electric vehicle (EV) adoption, can result in voltage deviations and power losses. To address these challenges, a Traffic Flow Capturing model is employed to maximize EV traffic flow and minimize active power loss (APL) and voltage deviation (VD). A novel hybrid metaheuristic algorithm (HGPC), combining Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Cuckoo Search Optimization (CO), is proposed to solve the multi-objective problem. The framework is validated on a 33-node DN and 25-node TN across three planning scenarios: DN-focused, TN-focused, and integrated TN-DN. In the DN-focused scenario, the objective is to minimize power loss, whereas in the TN-focused scenario, the goal is to maximize EV flow. In the integrated planning case, with battery constraints, the model achieves 155.05 kW APL and 41.54 % EV flow; without constraints, it improves to 148.14 kW APL and 57.52 % EV flow. These results confirm the effectiveness of the proposed HGPC algorithm, suggesting greater flexibility in handling conflicting multi-objective functions and highlighting the benefits of integrated planning for sustainable EV infrastructure.

Suggested Citation

  • Kumar, B.Vinod & M.A., Aneesa Farhan, 2025. "Multi-objective optimization framework for strategic placement of electric vehicle charging stations and shunt capacitors in a distribution network considering traffic flow," Applied Energy, Elsevier, vol. 397(C).
    • Handle: RePEc:eee:appene:v:397:y:2025:i:c:s0306261925010141
    DOI: 10.1016/j.apenergy.2025.126284
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    References listed on IDEAS

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    1. Chen, Zhibin & He, Fang & Yin, Yafeng, 2016. "Optimal deployment of charging lanes for electric vehicles in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 344-365.
    2. Vivalt, Eva & Coville, Aidan, 2023. "How do policymakers update their beliefs?," Journal of Development Economics, Elsevier, vol. 165(C).
    3. Kumar, B. Vinod & M.A., Aneesa Farhan, 2024. "Optimal allocation of EV charging station and capacitors considering reliability using a hybrid optimization approach," Applied Energy, Elsevier, vol. 375(C).
    4. Cavadas, Joana & Homem de Almeida Correia, Gonçalo & Gouveia, João, 2015. "A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 188-201.
    5. Bhatt, Brijesh & Singh, Anoop, 2020. "Stakeholders’ role in distribution loss reduction technology adoption in the Indian electricity sector: An actor-oriented approach," Energy Policy, Elsevier, vol. 137(C).
    6. Kuby, Michael & Lim, Seow, 2005. "The flow-refueling location problem for alternative-fuel vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 39(2), pages 125-145, June.
    7. Kong, Weiwei & Luo, Yugong & Feng, Guixuan & Li, Keqiang & Peng, Huei, 2019. "Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid," Energy, Elsevier, vol. 186(C).
    Full references (including those not matched with items on IDEAS)

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