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Topology and vulnerability of the Iranian power grid

Author

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  • Saniee Monfared, Momhammad Ali
  • Jalili, Mahdi
  • Alipour, Zohreh

Abstract

In this paper we investigated the structural properties of the ultra high voltage power transmission network of Iran. We modeled the power grid as a network with 105 nodes and 142 connection links. We found that the Iranian power grid displays a relatively moderate clustering coefficient–much larger than that of corresponding random networks–and small characteristics path length comparable to that of corresponding random networks; i.e. the power grid is a small-world network with exponential degree distribution. Global efficiency was considered as an indicator of grid’s performance and the influence of random and intentional nodal failures on the efficiency was investigated. We also studied the influence of cascaded failures on the largest connected component of the network. The power grid was vulnerable against cascaded failures, which should be considered serious in redesigning the network topology.

Suggested Citation

  • Saniee Monfared, Momhammad Ali & Jalili, Mahdi & Alipour, Zohreh, 2014. "Topology and vulnerability of the Iranian power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 24-33.
    • Handle: RePEc:eee:phsmap:v:406:y:2014:i:c:p:24-33
    DOI: 10.1016/j.physa.2014.03.031
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    References listed on IDEAS

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    Cited by:

    1. Al Khafaf, Nameer & Jalili, Mahdi, 2019. "Optimization of synchronizability in complex spatial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 46-55.
    2. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.
    3. Shahpari, Alireza & Khansari, Mohammad & Moeini, Ali, 2019. "Vulnerability analysis of power grid with the network science approach based on actual grid characteristics: A case study in Iran," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 14-21.
    4. Guo, Wenzhang & Wang, Hao & Wu, Zhengping, 2018. "Robustness analysis of complex networks with power decentralization strategy via flow-sensitive centrality against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 186-199.
    5. Yushu Sun & Xisheng Tang & Guowei Zhang & Fufeng Miao & Ping Wang, 2017. "Dynamic Power Flow Cascading Failure Analysis of Wind Power Integration with Complex Network Theory," Energies, MDPI, vol. 11(1), pages 1-15, December.
    6. Monfared, M.A.S. & Rezazadeh, Masoumeh & Alipour, Zohreh, 2022. "Road networks reliability estimations and optimizations: A Bi-directional bottom-up, top-down approach," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Kim, Dong Hwan & Eisenberg, Daniel A. & Chun, Yeong Han & Park, Jeryang, 2017. "Network topology and resilience analysis of South Korean power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 13-24.
    8. Espejo, Rafael & Lumbreras, Sara & Ramos, Andres, 2018. "Analysis of transmission-power-grid topology and scalability, the European case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 383-395.
    9. Fan, Wenli & Huang, Shaowei & Mei, Shengwei, 2016. "Invulnerability of power grids based on maximum flow theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 977-985.

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