基于序列模式挖掘的电力系统连锁故障模式分析方法

LIU Yuhang

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基于序列模式挖掘的电力系统连锁故障模式分析方法

更新时间：2025-08-13

- 基于序列模式挖掘的电力系统连锁故障模式分析方法
- Automation of Electric Power Systems Vol. 43, Issue 6, Pages: 34-40(2019)
- 作者机构：
  
  清华大学电机工程与应用电子技术系,北京市,100084
- 作者简介：
- 基金信息：
- DOI：
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- Published：2019
- 稿件说明：
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LIU Yuhang. [J]. Automation of electric power systems, 2019, 43(6): 34-40.
DOI：

LIU Yuhang. [J]. Automation of electric power systems, 2019, 43(6): 34-40. DOI：

摘要

研究连锁故障的传播规律，对于识别系统薄弱环节、制定连锁故障预防和阻断策略具有重要意义。在分析连锁故障发展过程的基础上，定义了连锁故障模式的概念，并基于序列模式挖掘技术提出连锁故障模式挖掘算法，实现对海量仿真数据的快速分析，有效辨识系统连锁故障模式。最后以IEEE 39节点系统和某省实际电网为例，利用该算法挖掘出系统主要连锁故障模式，并结合系统拓扑和潮流状态分析了系统连锁故障传播规律。测试结果证明，该方法对于分析系统连锁故障模式和辨识关键线路具有良好的效果。

Abstract

Studying the propagation mechanism of cascading failures is of great significance for identifying the vulnerable lines in power grid and formulating prevention and blocking strategies for cascading failures. Based on analyzing the development progress of cascading failures

the concept of cascading failure pattern is defined. A cascading failure pattern mining algorithm(CFPMA)based on sequential pattern mining technology is proposed to analyze massive simulation data and identify critical cascading failure pattern of power system. Finally

taking the IEEE 39-bus system and a real provincial power system for example

CFPMA is used to mine the main cascading failure patterns

and the cascading failure propagation law is analyzed by combining the power grid topology and power flow. The test results show that the proposed method has a good effect on identifying the main cascading failure patterns and the vulnerable lines.

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