Study On Integrated Method Of Scheduling And Control In Urban Rail Transit

ABSTRACT:Urban rail transit, as a modern transportation, has a large number of advantages, such as convenient and safe, comfortable and efficient, large freight volume, so it plays a positive role in alleviating urban traffic congestion. With the rapid development of urban rail transit, the problem of large energy consumption is drawing more and more attention. And for the unpredictability of passenger flow, delays of trains sometimes occur. Therefore, urban rail transit needs to further reduce energy consumption and to improve punctuality.Based on the utilization of recovery energy, this paper uses optimization theory which optimizes the timetable and the speed profiles simultaneously to study the integrated method of scheduling and control in urban rail transit. The paper puts forward a utilization strategy of the recovery energy among multi-trains, formulates an integrated model of scheduling and control, and designs a particle swarm optimization algorithm to solve the problem of energy-efficient operation and train’s adjustment. The research result of this paper enriches the train energy-saving optimization theory, and it also has certain reference significance for energy-saving operation of urban rail transit.(1) This paper studies the correlation between scheduling of trains and energy saving, controlling of trains and energy saving. Based on the mechanism of energy-saving control, the paper analyzes the relationship between energy consumption and control strategy. Based on the theory of regenerative braking and the absorption mechanism of energy-feedback, the paper analyzes the relationship between recovery energy and scheduling of trains.(2)This paper proposes a utilization strategy of the recovery energy among multi-trains. Firstly, unlike the existing works focusing attention on the successive trains, the paper studies the utilization of the recovery energy among multi-trains. Secondly, this strategy can be suitable for different sections, including short section and long section. Thirdly, the paper expands the scope of the utilization of recovery energy to the whole section, more than inbound phase.(3)Based on the proposed strategy, this paper formulates an integrated model of scheduling and control to statically optimize train operation. The model belongs to an integer programming model whose objective is to minimize net energy consumption. For one thing, the paper seeks the best coasting point to decrease the tractive energy. For another, the paper optimizes the overlapping time of accelerating phase and braking phase for multi-trains to increase the utilization of regenerative braking energy.(4)This paper proposes an integrated adjustment method of scheduling and control. When train operation is later than the planned timetable, static optimization scheme may no longer be energy-efficient. At that moment, the paper adopts the integrated adjustment method to dynamically adjust train operation. On the one hand, the paper mitigates the delays of trains by shortening the running time. On the other hand, the paper optimizes net energy consumption by energy-efficient strategy. Since energy and travel time exist the relation of interaction, the paper solves the Pareto optimal solution of energy and time.Based on the particle swarm optimization algorithm, this paper takes Beijing Yizhuang subway line and Beijing Changping subway line as examples to verify the efficiency of our model. The simulation results of Yizhuang line show that, compared with the current approach, the proposed approach can improve the utilization of regenerative energy by9.2%and reduce the total energy consumption by3.5%. And when delays of trains occur, integrated adjustment method can mitigate the delays of trains observably and provide better energy-efficient effect.