Study On Energy Consumption Estimation Of Urban Rail Transit System Considering Line Operation Characteristics

Urban rail transit, as a representative transportation mode of low pollution, low emission and high transport capacity, has become a priority to solve urban traffic problems. However, it is also facing more and more severe challenges with the rapid development at the same time. On the one hand, urban rail transit plays a more and more important role in the process of meeting the demand of urban residents travel, which has greatly eased the traffic pressure of the city. On the other hand, with the increasing of the total energy consumption of urban rail transit year by year, energy consumption has become an important problem to be solved urgently.In order to implement the energy conservation and emission reduction work of the transportation system, the transportation department needs to set a scientific and reasonable target for energy saving and emission reduction. So it is necessary to accurately estimate the energy consumption level of urban rail transit system. Considering the operation of different lines and analyzing the energy consumption level of urban rail transit system under the influence of line operation characteristics, it is the key to accurately estimate the traction energy consumption and the energy consumption of the station.The energy consumption estimation model of urban rail transit system is established based on the data of Beijing subway operation and energy consumption, which consider the external influence factors such as operation characteristics, season and temperature. The model can accurately estimate the energy consumption of urban rail transit system with different line types, and can provide reliable technical support for the development of energy saving and emission reduction targets. The results of the study are as follows:(1) This paper analyzes the composition of energy consumption in urban rail transit, and study the influencing factors of the traction and station energy consumption at the same time, through the induction and summary of historical statistical data and the existing research results. Finally, it concludes that in the process of building energy consumption model, the factors such as line operation index, season and temperature should be considered.(2) Taking into account the influence of line laying mode on the traction energy consumption, the line is divided into underground and ground line. With the help of the dynamic analysis of train operation, a nonlinear regression model based on dynamic equation is established for the underground and the ground line. Taking Beijing Metro as an example, the model is calibrated with the data of line operation and energy consumption statistics. And compared with the multiple linear regression model and BP neural network model, it is found that the nonlinear regression model based on the dynamic equation has good performance in prediction accuracy, goodness of fit and stability. In addition, the model can also take into account the speed of the train, making the model to explain the impact of factors more comprehensive.(3) The station is divided into two kinds:the underground station and the ground station, considering the influence of the station laying mode on the energy consumption of the station. The multiple linear regression model and BP neural network model for the energy consumption of the station are constructed respectively. It is concluded that the prediction precision of BP neural network model is better, through the comparison of the prediction accuracy and the goodness of fit of the two models.(4) For the existing lines, the operation indexes is predicted by ARIMA model and winters additive model. At last the operation energy consumption is estimated. And for the new lines, the operation index value can be forecasted by clustering method, which according to the similarity between the lines to establish the quantitative relationship between the existing line and the new line.Then get the operation energy consumption of the new line. Finally by the sum of energy consumption obtained the predictive value of the operation energy consumption for the railway network, and compared with the true value, which verifies the traction energy consumption and station energy consumption calculation model is effective.