A three-stage model of quantifying and analyzing power network resilience based on network theory

This paper introduces a novel three-stage analysis framework for investigating power network resilience in the face of failures. First, we introduce network modeling and resilience metrics, followed by an examination of network performance and restoration. The evaluation analysis is validated using IEEE118 and two generated small-world and scale-free networks, each consisting of 300 nodes, respectively. Our evaluation specifically focuses on assessing network resilience from both structural and functional perspectives. Simulation results have demonstrated that degree-based attacks have the most significant impact on reducing the size of the largest network component, while betweenness-based attacks lead to the fastest decrease in network efficiency. These findings have been further supported by percolation theory. Furthermore, the electrical-betweenness recovery strategy demonstrates superior performance compared to other recovery strategies. The proposed approach provides valuable insights for decision-makers in the development of mitigation techniques and optimal protection strategies.

Automated summary

This paper presents a novel three-stage analysis framework for investigating the resilience of power networks in the face of failures. The framework includes network modeling, resilience metrics, performance analysis, and evaluation. The study shows that degree-based attacks have the biggest impact on reducing network size, while betweenness-based attacks have the fastest decrease in network efficiency. The proposed approach provides valuable insights for decision-makers in developing mitigation techniques and optimal protection strategies.