The growing integration of DG enhances distribution network resilience, but existing centralized fault recovery strategies face critical limitations: excessive computational burdens on DCs and the insufficient utilization of local control capabilities, particularly with large-scale DG deployments. Current studies often fail to balance computational efficiency and dynamic recovery coordination between centralized and decentralized resources. To address the issue, a hierarchical control architecture is proposed that involves collaboration between the DC and LA energy gateways. By dynamically quantifying LA PSC through net power feasibility analysis, the framework optimizes network reconfiguration (DC level) and decentralized DG scheduling (gateway level). Validated on a modified IEEE 45-bus system, the strategy restored 7 MWh (4:00 fault) and 5 MWh (10:00 fault) of load, outperforming static methods by 26.9× in the mid-day case. While effective in urban grids, rural DG-sparse areas require future integration of mobile storage. The work balances centralized coordination and decentralized execution, offering a scalable resilience solution for modern networks.

The coordination of microgrid (MG) and distribution is an emerging trend for future development. This paper proposes an uncertainty feasible region (UFR) analysis method based on outer approximation cutting (OAC) under the coordination of MG and distribution. Firstly, an optimal economic dispatch scheduling is obtained. It serves as the basis for the intraday analysis of UFR. Drawing on the concepts of robust optimization, a method for determining the intra-day UFR is proposed. Subsequently, the problem is transformed using duality theory by identifying umbrella constraints, ultimately linearizing the problem to enable its solution by commercial software. In the intra-day analysis of the feasible region, the interactive power deviation between the MG and the upper-level grid (ULG) is allowed, which is represented by an interactive power deviation factor (IPDF). Different factors represent varying sizes of controllable resources, and a larger factor positively affects the size of the feasible region, and the volume is used to represent the size of the feasible region. The UFR defined in this paper provides a theoretical basis for renewable energy consumption capacity corresponding to the day-ahead dispatch scheduling. The effectiveness of the proposed method is validated by simulation results in a typical MG scenario.