电力系统自动化2011，Vol.35Issue(10)：42-47,6.
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
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.关键词
电网/分布式故障诊断/贝叶斯网络/D-S证据理论/级联跳闸Key words
power grid/ distributed fault diagnosis/ Bayesian network/ Dempster-Shafer evidence theory/ cascading trip引用本文复制引用
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):42-47,6.基金项目
国家电网公司科技项目"基于数据网的广域后备保护算法研究",中央高校基本科研业务费专项资金资助项目(SWJTU09ZT10). （SWJTU09ZT10）
