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

Abstract

• Investigate an integrated planning problem for electric-bus systems. • Incorporate muliple practical factors and requirements of electric-bus operations. • Develop robust optimization model to address energy consumption uncertainty. • Conduct empirical study in Singapore and provide managerial insights for operators. 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 en-route 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.