Research On The Optimization Method Of Train Energy-saving Operation Based On Multi-objective Artificial Bee Colony Algorithm

With the acceleration of China's urbanization process,urban rail transit has begun to be an important part of public transportation,and the corresponding energy consumption demand is increasing.Therefore,research on energy-saving technologies for train operation is of great significance.Based on the analysis of the research results of many domestic and foreign scholars,this paper has done the following work:(1)First,analyze the power supply system of urban rail transit,establish a DC traction power supply model.Study the force situation during train operation,establish the force model and motion equation of the train during operation,and calculate the energy consumption.(2)Second,study the optimized operation strategy and operation principle of single train,and establish the timing energy saving optimization model of single train.Elaborate the dynamic programming algorithm and analyze the solving rules to solve the single train timing energy optimization model.The simulation obtains the optimal running curve and control sequence of the train,and compares the energy consumption before and after the optimization to verify the effectiveness of the algorithm.(3)Then explain the principle of energy conversion and regenerative braking energy utilization in the traction substation.Study the method of calculating the DC traction power supply model by running section drawing method to obtain the calculation process of the traction energy consumption of the train.Establish a multi-vehicle and multi-objective energysaving optimization model.The optimization model was solved by using a multi-objective artificial bee colony algorithm,and the timetable data obtained by the solution is substituted into the calculation process of the running section drawing method to obtain the traction energy consumption data.Based on the data of Guangzhou Metro Line 7 and Line 9,simulation was performed to obtain the energy consumption of train traction before and after optimization and compared,to verify the effectiveness of the algorithm.(4)Finally,based on the timetable optimization results of Guangzhou Metro Line 7 and Line 9,conduct on-site energy consumption tests,elaborate the test plan,give the energy consumption test results,and analyze the reasons for the differences between the test and simulation results.