A Hybrid Data and Mechanism Model-driven Digital Twin Modelling Approach for Novel Traction Power Systems

Abstract Given the demand for real-time operation state simulation technology for integrating significant amounts of renewable energy into the traction power systems (TPSS), and considering the substantial volatility and intermittence of renewable energy (photovoltaic) output, the accuracy and real-time performance of traditional mechanism simulation models are low. This paper proposes a new digital twin (DT) modeling method for the TPSS, driven by a combination of data and mechanism models. Firstly, the mechanism model of the TPSS is established, with the external power supply simplified to a three-phase Thevenin equivalent circuit. The traction substation is replaced by a traction transformer, and the AT substation is replaced by an AT transformer. The traction network is simplified into a four-conductor model of T, F, P, and R, represented by a π-type equivalent circuit. Secondly, based on the measured data of photovoltaic (PV) power, the data are segmented according to its output time characteristics after preprocessing. The data source is derived by considering the form of a controlled current source. The PV data-driven model is established by importing the real-time data source into Simulink and outputting it to the controlled current source. Thirdly, the railway static power conditioner is used to effectively integrate the TPSS mechanism model with the PV data model, completing the coupling modeling of the two. Finally, the system is simulated and verified by modeling the typical working conditions of two power supply arms with heavy loads (8 MW) and one power supply arm with a heavy load (8 MW) and a light load (2 MW). The results show that the system can achieve the average distribution of power according to the external input PV output data and can reduce the traction energy consumption by about 0.5 MW for the two power supply arms. This is of great significance for the simulation and application of the novel TPSS.