Distributionally robust optimization configuration of integrated photovoltaic and energy storage in rail transit green energy system

In the context of carbon neutrality goals, the integration of distributed photovoltaics (DPV) and energy storage systems into high-speed railway traction substations contributes to improved energy self-sufficiency and emission reductions in rail transit. However, the inherent intermittency of DPV generation and the impulsive nature of traction loads present significant challenges to the safe and stable operation of the traction power supply system. To address these issues, this study proposes a novel planning framework for the co-deployment of DPV and hybrid energy storage systems (HESS) within an integrated rail transit green energy system, aiming to achieve synergistic coordination among the grid, generation, storage, and rolling stock. First, a grid-side three-phase voltage unbalance constraint is formulated based on power quality indices and linearized via a compensation strategy using the back-to-back converter. Second, a sliding window event detection algorithm is applied to extract high-speed train load profiles from field measurements, enabling minute-level dynamic traction load prediction through train diagram data. A two-stage distributionally robust optimization model is then developed to minimize the system's average daily total cost, accounting for uncertainties in DPV output and the cycle life degradation of lithium-ion batteries, while incorporating 1-min resolution safety constraints. The model is efficiently solved using an inexact column-and-constraint generation algorithm. Finally, a case study based on a high-speed railway substation in China validates the proposed approach, demonstrating a 22.74 % energy self-sufficiency rate, a 24.91 % reduction in costs, and a payback period of 3.26 years. The results confirm that the integration of DPV and HESS not only enhances energy efficiency and mitigates power quality issues, but also yields substantial economic benefits, offering a viable pathway toward low-carbon, high-quality, and cost-effective energy supply solutions for rail transit systems.