Timetable Optimization Model with Considering Regenerative Braking Power for Urban Rail

Along with China's economic growth and the urbanization is sped up. Energy conservation in urban rail transit (URT) has attracted widespread attention. Timely use of regenerative energy (URE) is an imperative way to save electricity. Regenerative braking, also known as feedback braking, is a braking technology used on electric vehicles to convert kinetic energy of train into electrical energy when the train is braking. Other trains could use these regenerative energy by accelerating in a cooperative way. In order to maximize the URE, this paper proposes a new approach that uses the train's electric power to gauge the available energy, and analyzes the operation process of a train to optimize the time when the train left the station. First, we defined 4 operating Modes of energy utilization, and codified an integer programming model. Second, we used a branch and bound algorithm to figure out the excellent result. Finally, we used the data on the operation of the Yanfang Line, Beijing Metro assessed the model. The simulation results illustrated that compared with the original timetable, the method can significantly improve the URE by 77.5%.