Robust optimization for integrated planning of electric-bus charger deployment and charging scheduling

Public transit (PT) operators have been replacing existing bus fleets with electric buses (EBs) to achieve carbon neutrality. To ensure a cost-effective EB operation with driving range anxiety, fast en-route charging technology has been adopted to recharge EBs during the dwell time. This study aims to determine an integrated robust planning for EB systems, by simultaneously optimizing enroute charger deployment, charging schedule and EB battery configuration, with the goal to minimize the total cost. A deterministic optimization model was first formulated that incorporates multiple practical factors such as weight-related energy consumption and charging capacity. Then we move forward to build robust optimization models to consider the energy consumption uncertainty. The developed models are transformed into equivalent and tractable formulations, which can be solved efficiently by off-the-shelf solvers. Lastly, numerical experiments demonstrate that the proposed models can provide an optimal and robust EB system planning solution for PT operators.

Automated summary

This study proposes a robust planning method for electric bus (EB) systems, considering multiple practical factors and energy consumption uncertainty, with the goal of minimizing total cost. Numerical experiments demonstrate that the proposed method can provide an optimal and robust solution for public transit operators.