Percolation theory-based resilience region definition method for integrated transmission-distribution network under extreme disasters scenarios

作者：Wei Liu, Lei Wang, Yulu Yang, Yannan Tuo, Kaiwen Hou, Chenghuang Wu, Jingzhe Wang, Jiyuan Tang · 发表于：Frontiers in Energy Research · 年份：2026 · DOI：10.3389/fenrg.2026.1672954 · 研究领域：Optimal Power Flow Distribution、Infrastructure Resilience and Vulnerability Analysis、Power System Reliability and Maintenance

With the continuous increase in power demand, the coupling between transmission and distribution networks has become increasingly close. Under extreme natural disasters, initial failures of a small number of components may trigger cascading failures in the integrated Transmission-Distribution Network (ITDN), eventually leading to large-scale system collapse. However, traditional microscopic resilience assessment approaches are inadequate for conducting unified quantitative analysis of such integrated systems. To address this issue, this paper proposes a unified resilience assessment framework from a macroscopic perspective by defining a two-dimensional resilient region for the ITDN. Specifically, the Monte Carlo method is employed to generate initial failure scenarios, and a percolation-based approach is used to simulate the progressive failure of components under random disturbances. The percolation threshold—defined as the critical failure fraction at which the system collapses—is adopted as a statistical indicator to quantify the system’s robustness. Furthermore, a line criticality index is constructed to identify vulnerable components, and the effectiveness of reinforcing the capacity of critical lines in enhancing system resilience is validated. Finally, simulation results based on the T6-D2 test system demonstrate that the proposed method can accurately delineate the resilience boundary of the coupled transmission-distribution network, providing theoretical support for ...