The Research On Energy Saving Optimization Method Of Multi-Train Cooperatvie Control

As a major transport measure, the urban rail guided transportation plays an important role in people’s lives. The trains of urban rail transit are mainly electrically drived. With the growth of transport capacity, the electricity consumption of the rail guided transportation is increasing rapidly. Energy saving has become one major research focusof urban rail transit.This paper studies the cooperative control methods of multiple trains for energy saving. The main points of the research include the train operation strategy, the use of regenerative braking energy, and the selection of multi-train energy saving optimization methods. The cooperatvie control model of muti-train track running is established with game theroy, which can select the optimized multi-train control strategy and reduce total energy consumption. It is important and meaningful for the energy-saveing optimization of the sustainable development of urban rail transit.The research contents of this paper are as follows:1、The study of the train energy saving optimization control method and regenerative braking. Combining with domestic and foreign research status, this paper aims to analyze the existing energy-efficient train operation theories, the principle of regenerative braking energy, the method of regenerative braking applied in multi-train cooperative control, which provides a theoretical foundation for the establishment of multi-train control model and the method of multi-train energy saving optimization.2、The application of game theory method in multi-train cooperative control. The train cooperative control is analyzed, followed with the introduction of game theroy. The adaptability of game theroy in the train operation control is also disscussed, which is implemented on the multi-train cooperative control.3、The establishment of the optimization model of energetic multi-train operation. The research on the method of multi-train energy-saving optimization based on game theory. The model includes the operation of the train, the utilization of regenerative braking energy, and the selection of energy saving optimization strategy with game theory. Considering constraints of time table and the application conditions of regenerative braking energy, the energy saving optimization scenario is analyzed systematically and comprehensively. The energy saving optimization strategy is also selected with game theory, which can achieve the goal of reducing the total energy consumption.4、The design of energy-saving statistical system and the verification of multi-train energy-saving effect. The development of the statistical system is based on the data of Beijing Subway Changping line, which also provides a verifying method. Compared with the exsiting train control stratagy, the performance of the multi-train energy-saveing optimization method is verified.According to the Beijing Changping Line subway line data,through the comparison of simulation analysis, the effect of energy saving is14.44%and the utilization rate of regenerative braking energy reaches as high as38.35%.