A two-layer construction of energy optimization approach for timetable

In urban rail transit system, utilization of the regenerative energy of trains is quite an efficient way for energy saving. This paper aims to reduce the total energy consumption of trains in a whole day by optimal utilization of the regenerative energy. The regenerative energy is generated by the braking trains, and in the same time used by the accelerating trains in the same power supply district. A two-layer construction is designed in this paper to solve the energy optimization problem. Firstly, in the upper layer we use genetic algorithm to distribute the running time of trains to every inter-stations; secondly, in the lower layer we calculate a velocity trajectory with tracking strategy in each inter-stations which is strictly closed to the distributed running time; thirdly, a simulation returns all the trains' energy consumption to the determination of GA, and finally achieves an energy optimized timetable of whole day. The simulation is based on the data gathered from Beijing Yizhuang Line, and cooperated with the tracking strategy of trains to ensure the accuracy of the running time and the energy consumption. The simulation result shows a better performance compared to the traditional methods.