Study On Optimization Of Energy Consumption Of Urban Rail Transit And Its Simulation Software Development

Rail transit plays an increasingly important role in the urban public transportation system, but it is also energy-intensive. There is great significance to develop an optimal train speed profile for energy-efficient train operation in both theoretical and practical aspects. Study on operation optimization of urban rail transit is to discuss how to minimize energy consumption in the condition of time limit and safety.Currently, there are several issues on domestic and foreign research: The optimization models of train operation were simplified in varying degrees and the complexity of the real track alignments were not fully taken into accout of. Most of the researches focused on the optimization of local points. Some researchers’ work had certain effects on energy saving while efficiency was sacrified. They are difficult to be applied to the practice. This thesis combines the theoretical analysis with computer simulation on the basis of the above study. The research emphasized on several aspects as below:1. The mechanical model of train movements and traction calculation model in the time-efficient mode is throughly analysised; the energy consumption based on the power of traction is established.2. A optimization model of energy consumption based on the traction calculation curve under the time-efficient mode is proposed. The track alignments is fully considered when setting the coasting points, which significantly reduces the waste of running time.3. The solution of braking points in traction calculation is improved, which greatly improves the stopping accuracy and makes it possible to parallelize traction calculation for multiple stations.4. A multiple agent parallelized simulated annealing algorithm is applied to solve the energy optimization problem. The simulation results show that the convergence is greatly upgraded.5. The visual simulation platform is designed and realized on the basis of above theorical study. The effectiveness of the proposed methods are verified by the platform.