| In recent years,in order to alleviate the “big city diseases” such as traffic congestion and environmental pollution,major cities are giving priority to public transport and green transport.In this context,electric buses(EBs)play a vital role in the structure optimization of urban transport with their advantages of large traffic volume,low emissions,and so on.The full promotion of EBs has become the trend in public transit both in terms of national policy and practical application.However,due to the limitation of battery capacity,EBs have many disadvantages such as short driving range,long charging time,and insufficient charging piles,which increase the difficulty of operation and management.In addition,the high purchase cost of the EB is also considered to be one of the problems that hinder the full promotion of EBs.Therefore,in order to solve the bottlenecks faced by EBs and promote the large-scale operation of EBs,this thesis proposes the research on the operation optimization of EBs with multiple vehicle types.The main work is as follows:(1)Research on the optimization of bus timetabling with multiple vehicle types.Aiming at minimizing travel cost for passengers and operating cost for providers,an optimization model is established.An algorithm is designed based on the enumeration idea to solve the model.Then,the optimal multi-vehicle-type timetable can be obtained.(2)Research on the optimization of the EB scheduling with multiple vehicle types based on a given multi-vehicle-type timetable.First,with consideration of differences in the purchase cost and driving range of EBs for multiple vehicle types,an optimization model is established to minimize annual total scheduling costs,including the fleet size,the number of charging piles,the deadheading distance and the empty seat penalty.Then,a two-stage heuristic procedure is developed to find the optimal solution considering recharging trips and the substitution between different vehicle types.(3)Research on the integrated optimization of timetabling and EB scheduling.An integrated optimization model is established by allowing slight adjustment of the optimal timetable.Then the two-stage heuristic procedure mentioned earlier is improved to solve the integrated optimization model.Through this process,a better EB scheduling and the corresponding timetable adjustment plan can be obtained.(4)The methodologies mentioned above are validated using a real-world transit network in Daxing District,Beijing.First,the optimization methods of timetabling and EB scheduling with multiple vehicle types are applied in sequence.Comparative analysis is conducted and indicates that the proposed methods performed in sequence have good application value.Then,sensitivity analysis reveals that the current recharging power(240k W)and discharging depth(80%)are approximately economical.Finally,the integrated optimization method is applied and analyzed.The result shows that the integrated optimization method can reduce the annual total scheduling costs by2.65% compared with the sequential one,due to slightly adjusting the departure time of some timetabled trips. |
