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An intelligent power grid emergency allocation technology considering secondary disaster and public opinion under typhoon disaster

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  • Wu, Wenjie
  • Hou, Hui
  • Zhu, Shaohua
  • Liu, Qin
  • Wei, Ruizeng
  • He, Huan
  • Wang, Lei
  • Luo, Yingting

Abstract

Typhoon disaster may not only cause power outage physically, but also breed negative sentiments in public opinion and affect social stability. Therefore, an intelligent power grid allocation technology considering secondary disaster and public opinion under typhoon disaster is proposed. Firstly, an Extra-Tree (ET) method is used to predict the power outage in time sequence (e.g., landing period, 6 h later, and 12 h later) after typhoon lands. Secondly, a typhoon secondary disaster potential assessment model is established based on disaster intensity and geographical environment. Since power outages may also cause public opinion polarization, a public opinion analysis model is proposed to mine Micro-blog (similar to Twitter) tweet information and analyze the demand for power restoration. Then, according to the results of secondary disaster potential assessment and public opinion analysis, the allocation strategy optimization is described as a Mixed Integer Nonlinear Programming (MINLP) problem. It is solved by the Stud Genetic Algorithm (Stud GA) and A-star path optimization algorithm. Finally, Yangjiang city in China under Typhoon “Chaba” (2022) is selected as the study area to verify the effectiveness and feasibility. It shows the proposed method can respond to public electricity demand in time and eliminate public negative sentiments, while the repair process is not disturbed by secondary disasters.

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  • Wu, Wenjie & Hou, Hui & Zhu, Shaohua & Liu, Qin & Wei, Ruizeng & He, Huan & Wang, Lei & Luo, Yingting, 2024. "An intelligent power grid emergency allocation technology considering secondary disaster and public opinion under typhoon disaster," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s0306261923014022
    DOI: 10.1016/j.apenergy.2023.122038
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    Cited by:

    1. Mao, Ding & Wang, Peng & Fang, Yi-Ping & Ni, Long, 2024. "Securing heat-supply against seismic risks: A two-staged framework for assessing vulnerability and economic impacts in district heating networks," Applied Energy, Elsevier, vol. 369(C).
    2. 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.
    3. Yao, Qi & Tang, Jie & Ke, Yiming & Li, Li & Lu, Xiaoqin & Hu, Yang & Fang, Fang & Liu, Jizhen, 2024. "Anti-tropical cyclone load reduction control of wind turbines based on deep neural network yaw algorithm," Applied Energy, Elsevier, vol. 376(PB).
    4. Lin, Yumian & Xiong, Houbo & Zhou, Yue & Wang, Tianjing & Lin, Yujie & Guo, Chuangxin, 2025. "Distributionally robust service restoration for integrated electricity-heating systems considering secondary strikes of subsequent random events," Applied Energy, Elsevier, vol. 380(C).

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