The city of Hamburg has decided to electrify its bus fleets. The two public transportation companies in this city expect to operate up to 1500 buses by 2030. In order to accomplish this ambitious goal, both companies need to build an appropriate charging infrastructure. They have both decided to implement the centralized depot charging concept. Buses can therefore charge only at the depot and do not have the possibility for opportunity charging at intermediate stations. The load profile of such a bus depot is highly dependent on the charging schedule of buses. Without an intelligent scheduling system, the buses charge on demand as soon as they arrive to the depot. This can lead to an unevenly distributed load profile with high load peaks, which is problematic for the local grid as well as for the equipment dimensioning at the depot. Charging scheduling on large-scale bus depots is a relatively new and poorly researched topic. This paper addresses the issue and proposes two algorithms for charging scheduling on large-scale bus depots with the goal to minimize the peak load. The schedules created with the proposed algorithms were both tested and validated in the Bus Depot Simulator, a cosimulation platform used for bus depot simulations.

Route scheduling is crucial for uninterrupted operation of modern bus fleets consisting of electric buses. This paper proposes an exact route scheduling optimization model for centralized bus depots based on mixed integer linear programming. In order to adjust to the current situation at many electric bus depots, the model considers a heterogeneous fleet consisting of multiple types of electric buses with different battery capacities. With additional charging scheduling the model can minimize the number of buses charging simultaneously which directly leads to load peak reduction. This allows considering further parameters, such as for example the grid capacity limit. The model can be used to minimize the necessary number of buses, to define the optimum composition of the fleet as well as to minimize the total cost of the fleet. The results show a clear cost advantage of operating a heterogeneous fleet as well as the benefits of combined route-and charging scheduling. Timetables from five real depots from the city of Hamburg in Germany were used as examples in this paper. Analysis of the proposed model using real data can provide a valuable input to other transportation companies preparing for the electrification of their fleet.

No abstract

No abstract

Owing to the immense climate changes in recent years, the city of Hamburg has decided to allow the purchase of only emission-free buses for public transportation. Meanwhile, Hamburg focuses on the implementation of electric buses. For this purpose, the two public transportation companies in Hamburg which are the Hamburger Hochbahn AG (HOCHBAHN), and the Verkehrsbetriebe Hamburg-Holstein GmbH (VHH) decided to build new charging infrastructure for electric bus depots. In addition, they started by electrifying their existing stations. This study proposes an optimal method for electrifying bus depots by