何小飞, 童晓阳, 孙明蔚. 基于贝叶斯网络和D-S证据理论的分布式电网故障诊断[J]. 电力系统自动化, 2011, 35(10): 42-47.
引用本文: 何小飞, 童晓阳, 孙明蔚. 基于贝叶斯网络和D-S证据理论的分布式电网故障诊断[J]. 电力系统自动化, 2011, 35(10): 42-47.
HE Xiao-fei, TONG Xiao-yang, SUN Ming-yu. Distributed Power System Fault Diagnosis Based on Bayesian Network and Dempster-Shafer Evidence Theory[J]. Automation of Electric Power Systems, 2011, 35(10): 42-47.
Citation: HE Xiao-fei, TONG Xiao-yang, SUN Ming-yu. Distributed Power System Fault Diagnosis Based on Bayesian Network and Dempster-Shafer Evidence Theory[J]. Automation of Electric Power Systems, 2011, 35(10): 42-47.

基于贝叶斯网络和D-S证据理论的分布式电网故障诊断

Distributed Power System Fault Diagnosis Based on Bayesian Network and Dempster-Shafer Evidence Theory

  • 摘要: 提出了基于贝叶斯网络和D-S证据理论的分布式电网故障诊断模型。首先采取实时接线分析方法确定故障区域以缩小诊断范围,然后分别运用蝶形和叶形分割法分割电网,再引入重合度概念,采用重合度、重合度与子网故障系数的几何平均值进行D-S证据融合。将2种电网分割法、2种D-S证据融合法组合成4种分布式诊断模式,再与集中式一起对多个算例进行对比仿真实验。仿真实验结果表明采用蝶形分割法和几何平均值法的分布式诊断模型较为准确和合理。

     

    Abstract: A novel distributed fault diagnosis model based on the Bayesian network and Dempster-Shafer(D-S) evidence theory is proposed.Firstly,a real-time wiring analysis method is used to determine the fault zones to narrow the diagnosis scope.Secondly,two kinds of segmentation method with butterfly and leaf are respectively adopted to reasonably divide the power grid.The concept of coincidence degree is introduced.The geometric mean of coincidence degree and fault coefficient of sub-grid is constructed for the fashioning of D-S evidence theory.Some examples are given for the centralized diagnosis,distributed diagnosis with two kinds of partitioning and two types of D-S evidence fashioning methods.The experimental results illustrate that the distributed fault diagnosis model with butterfly segmentation and geometric mean method is more accurate and reasonable.

     

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