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
孙明蔚;童晓阳;刘新宇;甄威;王晓茹;
摘要(Abstract):
电网故障时有大量报警产生,充分利用报警信号及其时序信息,处理好保护与断路器误动、拒动、信息缺失等不确定性情况,对于电网故障诊断显得非常重要。时序贝叶斯知识库(temporal Bayesian knowledge bases,TBKB)能够清晰表达多个事件之间的时序约束关系,并具备贝叶斯网络的推理能力。建立了基于TBKB的电网故障诊断模型,提出了元件故障与保护动作、保护动作与相应断路器跳闸等之间的时序因果关系(TCR)表达、时序约束一致性检查方法。根据电网结构,可先在线搜索出疑似元件,再对它们自动构造TBKB模型。针对信息缺失节点的状态进行假设,形成假设状态组合。针对这些状态组合,通过贝叶斯反向、正向推理,可判断故障元件,误动与拒动的保护与断路器。多个算例验证了该方法的有效性。
关键词(KeyWords): 电网故障诊断;时序贝叶斯知识库;时序约束
基金项目(Foundation): 国家自然科学基金项目(51377137,51377136)~~
作者(Author): 孙明蔚;童晓阳;刘新宇;甄威;王晓茹;
Email:
DOI: 10.13335/j.1000-3673.pst.2014.03.026
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