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Identification and vulnerability assessment of critical components in distribution networks under high penetration rate conditions

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  • Tang, Liangyu
  • Han, Yang
  • Zhou, Siyu
  • Zalhaf, Amr S.
  • Yang, Ping
  • Wang, Congling
  • Huang, Tao
  • Lu, Chang

Abstract

The power system, a cornerstone of modern infrastructure, is among the most complex artificial networks and plays a vital role in supporting global economic growth. In recent years, several large-scale blackouts worldwide have been triggered by cascading failures due to faults in critical components of the power system. This paper investigates the vulnerability of distribution networks characterized by high renewable energy penetration. Using complex network theory and power flow analysis, this paper thoroughly examines the vulnerability of distribution networks. Considering the uncertainty associated with the high proportion of renewable energy integration into the distribution network, this paper proposes the improved power flow betweenness (IPFB). It quantifies the contribution of critical components in the distribution network to power flow transmission between sources and loads. The index evaluates the vulnerability of critical components based on the distribution network's topology and operating states across various DG output scenarios. The results demonstrate a Pearson correlation coefficient greater than 0.97 between the proposed index and actual power flow distributions, confirming the reliability of the assessment.

Suggested Citation

  • Tang, Liangyu & Han, Yang & Zhou, Siyu & Zalhaf, Amr S. & Yang, Ping & Wang, Congling & Huang, Tao & Lu, Chang, 2025. "Identification and vulnerability assessment of critical components in distribution networks under high penetration rate conditions," Energy, Elsevier, vol. 318(C).
    • Handle: RePEc:eee:energy:v:318:y:2025:i:c:s0360544225005067
    DOI: 10.1016/j.energy.2025.134864
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    1. Naixuan Zhu & Guilian Wu & Hao Chen & Nuoling Sun, 2025. "Resilience Enhancement for Distribution Networks Under Typhoon-Induced Multi-Source Uncertainties," Energies, MDPI, vol. 18(13), pages 1-21, June.

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