Monte Carlo-Based Resilience Analysis of Traction Power Systems Integrated with PV and Energy Storage

The integration of renewable energy and energy storage (ES) into traction power networks has emerged as a major trend in rail transit, and resilience analysis of integrated power systems offers valuable insights for energy transition in transportation. This paper adopts resilience as a quantitative metric to evaluate the impact of critical component failures in railway traction power supply systems (TPSS) incorporating photovoltaic (PV) and ES technologies. A brief overview of PVstorage integration topologies is presented, followed by the development of a resilience evaluation framework based on three key dimensions: robustness, responsiveness, and recoverability. A resilience index calculation method based on the sequential Monte Carlo simulation is proposed. Failure rate data of each component are sampled according to an exponential distribution to randomly simulate system failures. The compensation effect of PV-storage during failures is analyzed, and the resilience index is calculated based on the simulated failure data. Comparative analysis reveals that the PV-storage integration scheme utilizing a railway power conditioner (RPC) connection demonstrates significantly higher resilience than the scheme employing a three-phase to two-phase V/v transformer. The resilience index system and the proposed calculation method in this study are of great significance for research on the integration of renewable energy into TPSS.