A risk-resistant microgrid formation method considering subsequent line faults and outage propagation

• Propose a MF method to restore DS considering subsequent faults and outage propagation. • Develop a detection method to detect potential on-outage area caused by outage propagation. • Introduce fictitious flow to prevent the occurrence of uncontrollable power supply areas. • Develop an ambiguity set for DRO-based MF optimization. Microgrid formation provides a viable solution for enhancing the resilience of distribution systems under extreme conditions. In general, the on-outage areas of the distribution system are partitioned into multiple islands to restore the critical loads after faults have occurred. However, the restored services could be interrupted by subsequent contingencies in extended extreme events with long-lasting destructive effects. To increase the risk resistance of formed microgrids, we propose an adaptive microgrid formation method that considers subsequent line faults and outage propagation. First, a strengthened ambiguity set of contingency probability distributions is constructed to depict the uncertainty of subsequent line faults. Moreover, a progressive detection mechanism is introduced to estimate outage propagation and identify the affected nodes following intentional islanding and fault isolation. Afterward, a three-layer distributionally robust optimization model is developed to maximize the expected load restoration with respect to the worst-case distribution of contingencies. The proposed distributionally robust optimization model is further transformed into a robust optimization model to facilitate the column-and-constraint generation algorithm. Simulation results validate the merits of the proposed method in improving the resilience of distribution systems during an extended extreme event by forming risk-resistant microgrids.