电网技术Issue(3)：715-722,8.DOI:10.13335/j.1000-3673.pst.2014.03.026
运用时序贝叶斯知识库的电网故障诊断方法
A Power System Fault Diagnosis Method Using Temporal Bayesian Knowledge Bases
摘要
Abstract
After the fault occurs in power grid, many alarm messages are generated. For power system fault diagnosis, it is important to utilize the alarms and their temporal information, and deal with the uncertainty such as mal-function, rejection and incompletion. The theory of temporal Bayesian knowledge bases (TBKB) can clearly express the temporal constraint relationship among multiple events, and possess Bayesian network’s reasoning ability. The TBKB-based power system fault diagnosis models were studied. The expression of temporal casual relationship (TCR) among fault components and protection operations and related breakers tripping are proposed. The consistency checking of TCR was studied, as well as on-line searching algorithm of suspicious components and automatic generating method of TBKB models. For the states of information missing, the state assumption is adopted to create hypothetic state combinations. For these states, Bayesian backward and forward reasoning is made to detect the fault component and identify mal-function and rejection of protections and breakers. The given examples have illustrated that the proposed fault diagnosis method is effective.关键词
电网故障诊断/时序贝叶斯知识库/时序约束Key words
power system fault diagnosis/temporal Bayesian knowledge bases/temporal constraint分类
信息技术与安全科学引用本文复制引用
孙明蔚,童晓阳,刘新宇,甄威,王晓茹..运用时序贝叶斯知识库的电网故障诊断方法[J].电网技术,2014,(3):715-722,8.基金项目
国家自然科学基金项目(51377137,51377136)。@@@@Project Supported by National Natural Science Foundation of China(NSFC)(51377137,51377136) （51377137,51377136）
