Resilient Distribution System Restoration: Managing Frequency Responses and Risk Mitigation in Extreme Events

With the increasing complexity of extreme event evolution process and the widespread integration of inverter-based DGs, distribution system (DS) restoration faces multiple risks such as subsequent faults and renewable energy output uncertainties. Neglecting these risks in restoration may lead to unexpected load shedding or even larger blackout. Existing works have not sufficiently considered these risks in DSs, especially cascading effect of subsequent faults. This paper proposed a DS restoration model considering the above two types of risks. Firstly, for subsequent faults, a node-microgrid affiliation identification model is designed to characterize the cascading process of “fault occurrence-protective device triggering-sudden frequency fluctuation” within each microgrid with flexible boundaries yet to be optimized. This facilitates the identification of DG status after subsequent faults and the integration of risk mitigation in restoration optimization. Secondly, for renewable energy uncertainties, robust constraints are formulated to ensure DG maintains necessary regulation capacity against renewable energy output deviations, preventing secondary interruption of the load already been restored. Finally, the model is formulated as a mixed-integer linear programming problem. Numerical results validated that the model can effectively avoid severe consequences while ensuring satisfactory restoration performance.