关键词: 城市交通, 行车调整, 邻域搜索, 列车运行图, 供电能力不足

Abstract: In urban rail transit systems, traction power supply faults often lead to the unidirectional power supply shortage in a local area, which seriously limits the total traction power and line capacity. Therefore, this paper proposes a train regulation approach based on dynamic power. Considering the instantaneous train power under different driving regimes, a 0-1 integer linear programming model is constructed to maximize the line capacity under the constraints of power supply capacity. Then, an adaptive large neighborhood search algorithm, based on the principle of "peak shaving and valley filling", is designed to improve the efficiency of traction power and to reduce the fault impacts. Finally, numerical examples based on the real data of Beijing Metro Line 7 are constructed to verify the effectiveness of the proposed approach. According to the simulation results, the computational time in all scenarios is controlled within 37.3 seconds, which satisfies the real-time requirement. After considering the dynamic power, the utilization rate of traction power becomes higher, which leads to the balance between power supply and demand, and increases the maintained line capacity by 59.3%~97.8% compared with the traditional approach based on maximum traction. For the performance of the designed algorithm, the gap from the optimal solution is less than 2.8%. Meanwhile, the solution quality is superior to the traditional neighborhood search algorithm.

Key words: urban traffic, train regulation, neighborhood search, train timetable, power supply shortage