Optimization Method for Mixed Vehicle Bus Scheduling Considering Scenario Differences
Pure electric bus has become an important option for the electric transformation of vehicles due to its low-carbon,energy-saving,and environmental protection characteristics.However,pure electric buses still face challenges such as performance degradation under low-temperature conditions and reduced mileage due to battery aging in actual operation.The mixed use of fuel buses and pure electric buses in operation helps to improve the performance degradation of pure electric buses in specific scenarios,and to enhance the efficiency and service quality of bus operation.This paper proposes a segmented optimization model for bus timetables considering the dynamic operation characteristics of buses.With the optimized frequency as input,a bus fleet scheduling planning compilation model is developed under mixed bus operation conditions.An improved genetic algorithm is designed to solve the model.Taking the bus routes in Beijing as an example,the case studies were conducted in different typical operational scenarios such as single-line operation,remote charging,and regional centralized scheduling to verify the applicability and optimization effect of the model under differentiated operational scenarios.The results indicate that compared to local charging scenarios,operational costs increased by 5.15%and the number of operating vehicles increased by 5.88%in remote charging scenarios.In the regional centralized scheduling scenario where multiple routes are jointly scheduled,operational costs decreased by 4.68%compared to single-line operation scenarios.Under the condition of given bus types proportion threshold,the effectiveness of mixed vehicle operation surpasses single vehicle type operation,effectively reducing operational costs and carbon emissions.This study provides a support for public transport enterprises to create scientific and flexible electric bus operation scheduling schemes based on different operation scenarios.
urban trafficbus scheduling optimizationgenetic algorithmmixed bus typespure electric busscheduling plan
NETL
NSTL
万方数据
