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Related Experiment Video

Updated: Feb 25, 2026

Author Spotlight: Impact of Physical Barriers on Rodent Populations in Farmland Areas

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Published on: March 8, 2024

Fault-Chain-Based Prevention and Control Method for Typhoon Disaster.

Yongqiang Gao¹, Jialu Li¹, Hengdao Guo²

¹China Southern Power Grid.

Journal of Visualized Experiments : Jove

|February 23, 2026

Summary

This summary is machine-generated.

This study introduces a fault-chain method to prevent power grid failures during typhoons. It identifies high-risk branches and optimizes controls to minimize load shedding and costs, enhancing grid stability against extreme weather.

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Area of Science:

Power Systems Engineering
Disaster Management
Risk Assessment

Background:

Extreme weather events like typhoons threaten power grid stability.
Conventional N-1/N-2 security criteria are insufficient for correlated, probabilistic failures.
Proactive disaster prevention and control are crucial for resilient power grids.

Purpose of the Study:

To develop a fault-chain-based method for typhoon disaster prevention in power grids.
To address limitations of traditional security criteria in extreme weather scenarios.
To enhance the operational integrity and stability of power grids.

Main Methods:

Integrated typhoon wind field and transmission branch vulnerability models to quantify failure probabilities.
Identified high-risk branches and performed systematic fault chain searches for cascading outages.
Developed a risk-oriented preventive control optimization model coordinating generator outputs and load shedding.

Main Results:

Effectively captured typhoon-induced power grid failure characteristics.
Significantly reduced expected load curtailment compared to traditional methods.
Demonstrated reduced control costs and enhanced grid resilience under typhoon conditions.

Conclusions:

The proposed fault-chain method offers a practical and economical decision-support tool for power grid operation during typhoons.
The method improves power grid stability and reduces economic losses from extreme weather events.
Provides a robust approach for managing risks associated with spatially correlated failures in power systems.