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Cascade failure analysis of power grid using new load distribution law and node removal rule

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  • Ren, Hai-Peng
  • Song, Jihong
  • Yang, Rong
  • Baptista, Murilo S.
  • Grebogi, Celso

Abstract

The power grid is a directional complex network of generators, substations, and consumers. We propose a new load distribution law to emulate the power grid. We assume that the power flow is transferred through all the paths connecting generators and consumers according to their efficiency. The initial generation of generators and the initial loads of substations are calculated according to the path efficiency and the load of the consumers. If a node fails, it is removed from the power grid, and all paths passing through it will fail to transfer power. In that case, the loads of the corresponding consumers are redistributed within the whole network. During the failure cascading and propagation procedure, our node removal rule is to remove the first overload node along the opposite direction of power flow, then the network distributes load and goes on the cascade procedure. Our new removal rule for nodes does suppress the large scale cascading failures. This work would be very helpful for designing the protective relay system and the tolerant parameters of the grid.

Suggested Citation

  • Ren, Hai-Peng & Song, Jihong & Yang, Rong & Baptista, Murilo S. & Grebogi, Celso, 2016. "Cascade failure analysis of power grid using new load distribution law and node removal rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 239-251.
    • Handle: RePEc:eee:phsmap:v:442:y:2016:i:c:p:239-251
    DOI: 10.1016/j.physa.2015.08.039
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    References listed on IDEAS

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    Cited by:

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    2. Darui Zhu & Haifeng Wang & Rui Wang & Jiandong Duan & Jing Bai, 2022. "Identification of Key Nodes in a Power Grid Based on Modified PageRank Algorithm," Energies, MDPI, vol. 15(3), pages 1-15, January.
    3. 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.
    4. Arinushkin, P.A. & Vadivasova, T.E., 2021. "Nonlinear damping effects in a simplified power grid model based on coupled Kuramoto-like oscillators with inertia," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    5. Guo, Hengdao & Zheng, Ciyan & Iu, Herbert Ho-Ching & Fernando, Tyrone, 2017. "A critical review of cascading failure analysis and modeling of power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 9-22.
    6. Zhou, Jian & Huang, Ning & Coit, David W. & Felder, Frank A., 2018. "Combined effects of load dynamics and dependence clusters on cascading failures in network systems," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 116-126.
    7. Ma, Min & Hu, Dawei & Chien, Steven I-Jy & Liu, Jie & Yang, Xing & Ma, Zhuanglin, 2022. "Evolution assessment of urban rail transit networks: A case study of Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    8. 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.
    9. Zhou, Jian & Coit, David W. & Felder, Frank A. & Wang, Dali, 2021. "Resiliency-based restoration optimization for dependent network systems against cascading failures," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    10. Yang, Li-xin & Jiang, Jun & Liu, Xiao-jun, 2021. "Synchronous patterns of oscillatory power network with general coupling matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).

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