Resilient Mitigation Strategy for Networked DC Microgrids Under Uncertainties

Microgrids have emerged as a promising solution to improve the resilience and reliability of power systems. However, unexpected faults can still pose significant challenges to the stable operation of microgrids. This paper proposes a stochastic programming-based strategy for mitigating faults in a DC microgrid. First, a scheduling strategy is implemented for normal operations and switched to a mitigation strategy upon detecting faults, which ensures optimal performance and resilience. Second, a scenario-based stochastic programming enhanced by the DBSCAN algorithm for scenario reduction is designed, which addresses the optimization problem efficiently. Comprehensive simulations are conducted to evaluate the proposed scheduling and mitigation strategies, demonstrating their advantages under both normal and fault conditions.