TY - JOUR
T1 - A three-stage model of quantifying and analyzing power network resilience based on network theory
AU - Wang, Shuliang
AU - Guo, Zhaoyang
AU - Huang, Xiaodi
AU - Zhang, Jianhua
N1 - Publisher Copyright:
© 2023
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - Network theory
KW - percolation theory
KW - resilience assessment
KW - restoration strategy study
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U2 - 10.1016/j.ress.2023.109681
DO - 10.1016/j.ress.2023.109681
M3 - Article
SN - 1879-0836
VL - 241
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 109681
ER -