A Resilience-Oriented Method for Identifying Critical Lines in Active Distribution System

As the risks of malicious cyber-physical attacks continue to escalate, there is an urgent need to enhance the resilience of active distribution systems with large-scale distributed generation (DG) against such high-impact, low-frequency events. The identification of critical lines plays a crucial role in the planning and operation of distribution systems, motivating the development of a resilience-oriented identification method to protect the system from extreme events. Therefore, a tri-level optimization model is proposed to identify critical lines, incorporating attack resources, optimal attack strategies, and optimal protection strategies. Furthermore, a model based on distributionally robust optimization (DRO) is introduced to account for the distributional uncertainty of attack resources within the identification framework. A proper algorithm is employed to address the complex optimization of the multi-level DRO-based model. Finally, a significance index is proposed to evaluate the importance of critical lines. Numerical studies conducted on the IEEE 33-bus distribution system confirm the feasibility of the proposed method. Moreover, the results demonstrate that the proposed method provides a robust ranking of power lines, which can assist operators in enhancing the resilience of active distribution networks.