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<p>Electric vehicles (EVs) play a crucial role in advancing sustainable transportation, reducing greenhouse gas emissions, and diminishing reliance on fossil fuels. However, the increasing adoption of EVs presents challenges for power systems, especially in areas with high EV concentrations, necessitating infrastructure upgrades. To address these challenges, this study focuses on determining the optimal number of rental centers and the maximum number of EVs per center to aid policymakers. By analyzing travel behavior using a fleet of 140&#xa0;EVs, the study establishes per-unit profiles and total fleet loads. Particle Swarm Optimization (PSO) is utilized to optimize the locations of rental centers and fleet sizes, ensuring compliance with voltage constraints. Simulations are performed on a modified IEEE 33-bus test system, and sensitivity analyses are conducted on key parameters to assess their impact on the optimal solution. This research aims to provide policymakers with insights for allocating permits to EV rental centers, facilitating the successful integration of EVs into transportation systems.</p>

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Optimizing Electric Vehicle Rental Services: Identifying Optimal Size and Locations for Permitting

  • 期刊论文

  • 发表日期：

    2025年12月15日

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  • Abdulaziz Almutairi

摘要

Electric vehicles (EVs) play a crucial role in advancing sustainable transportation, reducing greenhouse gas emissions, and diminishing reliance on fossil fuels. However, the increasing adoption of EVs presents challenges for power systems, especially in areas with high EV concentrations, necessitating infrastructure upgrades. To address these challenges, this study focuses on determining the optimal number of rental centers and the maximum number of EVs per center to aid policymakers. By analyzing travel behavior using a fleet of 140 EVs, the study establishes per-unit profiles and total fleet loads. Particle Swarm Optimization (PSO) is utilized to optimize the locations of rental centers and fleet sizes, ensuring compliance with voltage constraints. Simulations are performed on a modified IEEE 33-bus test system, and sensitivity analyses are conducted on key parameters to assess their impact on the optimal solution. This research aims to provide policymakers with insights for allocating permits to EV rental centers, facilitating the successful integration of EVs into transportation systems.