Randomized trial investigates operational strategies for electric bus charging stations, suggesting improved efficiency and reduced user wait times.
Key Points
This research aims to optimize the operation of electric bus charging stations to enhance efficiency for both electric buses and private electric vehicles.
Developed a bi-level optimization model to analyze interactions between electric bus firms and private electric vehicles.
Utilized a multiple-population genetic algorithm to solve the optimization model.
Conducted experiments comparing dynamic optimization strategies against fixed strategies in various scenarios.
Achieved over 80% utilization of charging resources, maintaining PEV user wait times under 0.5 hours.
Dynamic optimization improved operational efficiency compared to fixed strategies, especially with lower transition costs.
The proposed algorithm outperformed traditional genetic algorithms in 50 experiments.