Study Of Electric Bus Travel Plans Considering Charging Continuity And Demand Response

Electric buses provide a sustainable way for passengers to travel and have the advantages of zero emissions,affordability and energy savings.However,the range of electric buses is limited compared to traditional fuel buses,which means that most electric buses are difficult to run continuously without recharging.With the rapid development of public transportation in China,there is an increasing trend toward personalization and the emergence of demandresponsive buses to meet the requirements of many passengers,but the introduction of electric buses into demand-responsive systems has rarely been reported.At the same time,the study of electric bus travel plans that respond to real-time demand is important for improving the overall service quality of public transportation systems and reducing residents’ travel costs.Based on the above background,thesis investigates the electric bus travel plan considering charging continuity and demand response,and the main work is as follows:(1)For the conventional fixed-point and fixed-route electric bus travel planning problem,we design the unplugging number constraint that portrays the charging continuity and the flexible initial power setting,and use the time-discrete modeling method to formulate the problem as a mixed-integer planning model with the objective of minimizing the total operating cost,and solve it by using CPLEX.The optimization results for the Davis,California case show that the exact solution is computed in about 1800 seconds for a 13-route,440-trip task bus network.Sensitivity analysis shows that the flexible initial power setting with a range of 270-300 km reduces the charging time by more than 5% on average compared to the fixed initial power setting,and the operation management suggests that the fixed initial power setting is approximately the minimum cost at 70% of the maximum battery capacity,and the unplugging frequency constraint significantly reduces the unreasonable charging operation by more than80%.This thesis also conducts a sensitivity analysis for different battery capacities and different tariff scenarios.(2)For the demand-responsive electric bus travel planning problem,the optimal field departure time for electric bus vehicles,the station visit sequence in the vehicle travel route,and the charging scheduling scheme for electric buses are optimized.The objective is to minimize the electric bus vehicle travel cost,passenger fare discount cost and charging cost.This thesis designs a simulated annealing algorithm based on a variable neighborhood to solve the model,and uses the Beijing Huilongguan community road network for numerical experimental analysis,and compares the optimization results and operational efficiency under different combinations of internal algorithms;sensitivity analysis shows that as the fleet size increases,the average route length decreases while the average charging cost and charging frequency of each route decrease.The total cost and number of charges increase as the demand increases.(3)For the electric bus travel planning problem that responds to real-time demand,a dynamic algorithm is designed based on the demand-responsive electric bus travel planning problem,which is based on a rolling time-domain strategy to transform the online dynamic problem into a multi-stage offline static problem,and then each static demand-responsive electric bus travel planning model is solved separately using a simulated annealing algorithm.The effect of the algorithm on dynamic scheduling is demonstrated using case studies and sensitivity analysis of the parameters.The results of the study can provide theoretical guidance for real-time vehicle scheduling of public transportation.