Optimal dispatching and charging plans in electrified bus networks

Battery Electric Buses often require daytime charging. Their unavailability during non-negligible charging window significantly increases the fleet size. Here, we show that we can reduce the fleet size by modifying the Trip Assignment Criteria and reduce the total idle time between the trips. The proposed urban-scaled model can also find the optimal number of charging stations. We used complex networks approach and mathematical programming to develop two adjoined graph-based algorithms. The Restricted Minimum Weight Matching algorithm minimizes the fleet size considering the electrification constraints. The Smooth Load Distributing algorithm maximizes the total energy delivered to the batteries with a minimum load applied to the electrical grid. Both algorithms are P-class and can solve the problem. We applied the model to Sydney in Australia and Birmingham in UK and showed that it can significantly reduce the fleet size and the number of charging stations for these metropolises.