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<p>Wind disasters often cause widespread power outages, posing a serious threat to the safe operation of cities. This article systematically reviews key advances in early warning research on wind-induced power outages based on the framework of risk source, risk exposure, and risk mitigation. For risk sources, existing studies focus on wind load forecasting and the mechanisms that induce tree failure. For risk exposure, research has matured in analyzing wind-induced transmission and distribution circuit failures, while critical node identification and fault-propagation modeling have garnered extensive interest. For risk mitigation, the application of physical reinforcing, network reconfiguration, emergency power deployment, and intelligent dispatch has markedly strengthened pre-event preparedness and mid-event response. However, several gaps remain in current research. (1) Wind-field modeling often relies on stationary-wind assumptions and single-parameter meteorological inputs, making it difficult to capture the complexity of dynamic processes under evolving, nonstationary typhoon winds. (2) In the urban environment, the cascading faults in the fault propagation mechanism of the power system have not yet been fully analyzed. (3) Power outage prediction models rely on static data and analysis of isolated variables. Mainstream machine learning methods overly focus on historical data fitting while neglecting the physical consistency of the disaster process. (4) Mitigation strategies often emphasize localized hardening and post-event response, lacking pre-disaster resilience planning and system design.</p>

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Wind-Induced Electric Power Interruption: A Review of Risk Source, Risk Exposure, and Risk Mitigation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月27日

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  • Jingwei Fu,
  • Donglian Gu,
  • Zhen Xu,
  • Qingrui Yue

摘要

Wind disasters often cause widespread power outages, posing a serious threat to the safe operation of cities. This article systematically reviews key advances in early warning research on wind-induced power outages based on the framework of risk source, risk exposure, and risk mitigation. For risk sources, existing studies focus on wind load forecasting and the mechanisms that induce tree failure. For risk exposure, research has matured in analyzing wind-induced transmission and distribution circuit failures, while critical node identification and fault-propagation modeling have garnered extensive interest. For risk mitigation, the application of physical reinforcing, network reconfiguration, emergency power deployment, and intelligent dispatch has markedly strengthened pre-event preparedness and mid-event response. However, several gaps remain in current research. (1) Wind-field modeling often relies on stationary-wind assumptions and single-parameter meteorological inputs, making it difficult to capture the complexity of dynamic processes under evolving, nonstationary typhoon winds. (2) In the urban environment, the cascading faults in the fault propagation mechanism of the power system have not yet been fully analyzed. (3) Power outage prediction models rely on static data and analysis of isolated variables. Mainstream machine learning methods overly focus on historical data fitting while neglecting the physical consistency of the disaster process. (4) Mitigation strategies often emphasize localized hardening and post-event response, lacking pre-disaster resilience planning and system design.