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Distributionally Robust Microgrid Formation Approach for Service Restoration Under Random Contingency

When a major outage occurs in a distribution system due to extreme events, service restoration (SR) strategies pick up critical loads after isolating the faults that have occurred. However, in extreme conditions, traditional SR strategies could pose potential security risks to restored services due to subsequent contingencies in succeeding events. To address this challenge, we propose a microgrid-based SR methodology that aims to enhance the preparedness of microgrids during unfolding extreme events. The proposed SR strategy comprises microgrid formation (MF) and sequential service restoration (SSR) steps. The MF makes the benefit of topology switching, generator allocation, and load demand response. Additionally, the uncertainty of line failure probability is considered, and a distributionally robust optimization model is proposed to maximize the expected load restoration with regard to the worst-case distribution of contingencies. Then, the SSR is formulated as a mixed-integer linear program model to yield proper load switching sequences and generation of power sources for sequentially restoring the outage system. The proposed SR measure enhances the system resilience by the proactive formation of microgrids, reducing the impact of cascading phenomenon when lines with high failure probability are tripped. The effectiveness of the proposed method is validated by numerical simulations.