It is difficult to determine the source of large-scale power outages, and there are problems such as low accuracy in calculating the probability of power failures, poor consistency in evaluation, and long time required for risk assessment. Therefore, a scenario based automatic risk assessment method for large-scale power outages is proposed. The article first analyzes various factors that lead to large-scale power outages, including natural external damage, human error, internal system operation problems, and inadequate management. In response to these factors, the article provides a detailed introduction to a new risk assessment method. This method calculates the comprehensive probability of power line breakage and tower collapse, and combines scenario construction techniques to evaluate the degree of danger of large-scale power outages. The experimental results show that the proposed method has high accuracy in calculating the probability of power failures, good consistency in evaluation, and short time required for risk assessment.

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Risk Assessment of Large-Scale Power Outages Under the Concept of Scenario Construction

  • Aqin Wu,
  • Wei Ke,
  • Xiong Zhou,
  • Xin Yu,
  • Zhiguang Yu

摘要

It is difficult to determine the source of large-scale power outages, and there are problems such as low accuracy in calculating the probability of power failures, poor consistency in evaluation, and long time required for risk assessment. Therefore, a scenario based automatic risk assessment method for large-scale power outages is proposed. The article first analyzes various factors that lead to large-scale power outages, including natural external damage, human error, internal system operation problems, and inadequate management. In response to these factors, the article provides a detailed introduction to a new risk assessment method. This method calculates the comprehensive probability of power line breakage and tower collapse, and combines scenario construction techniques to evaluate the degree of danger of large-scale power outages. The experimental results show that the proposed method has high accuracy in calculating the probability of power failures, good consistency in evaluation, and short time required for risk assessment.