Applying a hybrid model considering the interaction between train and power system for energy consumption surveys

Abstract

Abstract Power supply system plays an important role in the operation of urban rail systems. It has to provide high‐quality energy for trains continuously. Train's energy consumption is varied directly with operation conditions such as train's headway, train configuration, line characteristic and many other factors. Therefore, using a powerful simulation tool for estimating energy consumption considering these factors seems inevitable. This paper tries to develop a hybrid model in which the train model is based on acquired data from real measurement and an adapted network electrical model. Train empirical model is based on neural network on the basis of online data measured in line one of Shiraz metro and used for training of model. Then benefiting from optimization algorithms, a novel model of energy supply system of trains, including Traction Substations (TSS) and Overhead Catenary System (OCS), is proposed. Finally, the behaviour of trains during operation in 15‐min headway was simulated and the results under same conditions were compared with practical measurements. Currently, this model helps to determine power system behaviour during different operation conditions, predicting energy consumption for different headways, Train's driver behaviour during acceleration, deceleration and braking and also operation risk analysis during traction substations outages.