Bilevel Optimal Scheduling of Electric Bus Fleets in Regional Integrated Electricity-Gas-Heat Energy Systems

Proliferation of electric buses (EBs) is widely acknowledged as a viable solution to reduce carbon emissions while addressing the demands of ground transportation. This article investigates how to optimally schedule EBs in regions where heterogeneous energy resources, such as electricity, gas, and heat, are integrated as a regional integrated energy system (RIES). A novel bilevel optimal scheduling framework considering EBs' operation schedules and vehicle-to-grid (V2G) responses is proposed in this work. First, instead of charging-by-need (e.g., low SOC), this article considers charging-by-scheduling (e.g., low electricity price) to optimize the regional energy cost by explicitly incorporating coupled constraints from EB operation schedules, renewable energy generations, gas network models, and heat supply demands. The upper level scheduling strategy is formed to minimize the operation cost of the entire RIES. Second, EB operation strategies, and energy generation and heat conversion devices (e.g., combined-heat-and-power (CHP), electric boilers, and gas boilers) are further optimized in the lower level to minimize fluctuation in the total electrical load. Finally, numerical simulation results of coordinated scheduling of EB charging, renewable integration, and gas supply to meet electrical and heat demands under different scenarios are compared and analyzed. Simulation results based on five scenarios show that the bilevel model and the two-stage optimal scheduling method can realize the optimal operation cost and reduce the electrical load fluctuation of the system.

Automated summary

This article investigates how to optimally schedule electric buses (EBs) in regions where heterogeneous energy resources are integrated as a regional integrated energy system (RIES). A novel bilevel optimal scheduling framework considering EBs' operation schedules and vehicle-to-grid (V2G) responses is proposed. Simulation results based on five scenarios show that the bilevel model and the two-stage optimal scheduling method can realize the optimal operation cost and reduce the electrical load fluctuation of the system.