Optimizing electric bus charging infrastructure considering power matching and seasonality

In this research, a novel optimization model for electric bus charging station location, charger configuration, charging time and vehicle flow is developed considering power matching and seasonality. The seasonality highlights the effect of air temperature on the battery performances of electric buses. Power matching between batteries and chargers jointly determines the maximum battery acceptance rates of electric buses, and this consideration results in nonlinear constraints. A surrogate-based optimization approach is proposed to solve the mixed integer nonlinear program efficiently. The optimization model is demonstrated on a sub-transit network including 17 bus lines in Beijing. The results reveal significant performance differences regarding vehicle scheduling and charging among different bus fleets in the BEB-based transit system. The interesting findings on the distribution of vehicle flows for charging provide strong evidence to consider powering match in the bus charging infrastructure layout.

Automated summary

This research introduces a novel optimization model for electric bus charging station location, charger configuration, charging time, and vehicle flow considering power matching and seasonality. A surrogate-based optimization approach is used to efficiently solve the mixed integer nonlinear program, revealing significant performance differences in vehicle scheduling and charging among different bus fleets in a Beijing-based transit system. Interesting findings on the distribution of vehicle flows for charging provide strong evidence to consider power matching in the bus charging infrastructure layout.