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Fast dynamic identification algorithm for key nodes in distribution networks with large-scale DG and EV integration

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Listed:
  • Liu, Haiquan
  • Zhou, Suyang
  • Gu, Wei
  • Zhuang, Wennan
  • Zhou, Aihua
  • Peng, Lin
  • Liu, Meizhao

Abstract

The increasing penetration of distributed generators and electric vehicles (EV) in distribution networks has significantly impacted their safe and stable operation. To enhance the reliability of distribution networks and improve their emergency response capabilities, this paper proposes a fast dynamic identification algorithm (FDIA) for key nodes in distribution networks. Firstly, we characterized the dynamic characteristics of conventional loads and the spatiotemporal transfer features of EV loads in the distribution network. We proposed a method to represent the vulnerability of network nodes and defined a network fault linkage matrix that reflects the dynamic impact on node voltage. Subsequently, we utilized hidden fault nodes to characterize the uncertainties in the actual operation of the power grid, forming a derivative network and its correlation matrix. Based on an improved PageRank algorithm, and in conjunction with the derivative network correlation matrix, we designed an FDIA for key nodes. Finally, we applied the FDIA to the modified IEEE 33-bus system and a real 186-bus distribution network system in a region of China for validation. The results indicate that the overall identification time for FDIA is only 17.94 s, and the identification accuracy reaches 95 %, confirming the effectiveness and feasibility of FDIA. This study provides a new perspective for the dynamic identification of critical nodes in distribution networks under new power systems.

Suggested Citation

  • Liu, Haiquan & Zhou, Suyang & Gu, Wei & Zhuang, Wennan & Zhou, Aihua & Peng, Lin & Liu, Meizhao, 2025. "Fast dynamic identification algorithm for key nodes in distribution networks with large-scale DG and EV integration," Applied Energy, Elsevier, vol. 388(C).
    • Handle: RePEc:eee:appene:v:388:y:2025:i:c:s0306261925003381
    DOI: 10.1016/j.apenergy.2025.125608
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    References listed on IDEAS

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    1. Su, Qingyu & Chen, Cong & Huang, Xin & Li, Jian, 2022. "Interval TrendRank method for grid node importance assessment considering new energy," Applied Energy, Elsevier, vol. 324(C).
    2. Bloess, Andreas, 2019. "Impacts of heat sector transformation on Germany’s power system through increased use of power-to-heat," Applied Energy, Elsevier, vol. 239(C), pages 560-580.
    3. Gondia Sokhna Seck & Vincent Krakowski & Edi Assoumou & Nadia Maïzi & Vincent Mazauric, 2020. "Embedding power system's reliability within a long-term Energy System Optimization Model: Linking high renewable energy integration and future grid stability for France by 2050," Post-Print hal-02418375, HAL.
    4. Gao, Xin & Ye, Yunxia & Su, Wenxin & Chen, Linyan, 2023. "Assessing the comprehensive importance of power grid nodes based on DEA," International Journal of Critical Infrastructure Protection, Elsevier, vol. 42(C).
    5. R. Kinney & P. Crucitti & R. Albert & V. Latora, 2005. "Modeling cascading failures in the North American power grid," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 46(1), pages 101-107, July.
    6. Seck, Gondia Sokhna & Krakowski, Vincent & Assoumou, Edi & Maïzi, Nadia & Mazauric, Vincent, 2020. "Embedding power system’s reliability within a long-term Energy System Optimization Model: Linking high renewable energy integration and future grid stability for France by 2050," Applied Energy, Elsevier, vol. 257(C).
    7. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    Full references (including those not matched with items on IDEAS)

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