胡江;赵冬梅;张旭;刘志伟;

• 1:华北电力大学电气与电子工程学院
• 2:朔州供电公司

摘要(Abstract)：

随着电网调控一体化的全面推进,针对低价值密度故障数据的有效诊断成为实现电网自愈化的关键。该文提出了一种基于最大熵隐马尔科夫模型(maximum entropy hidden Markov model, ME-HMM)的电网故障诊断方法,该方法首先对调度中心所接收到的遥信信息进行去噪解析,并基于保护-断路器关联关系定义了待诊断信息类型以及异常信息模式,然后结合电气量信息和开关量信息构建特征函数向量,并通过训练ME-HMM模型对故障数据所隐藏的异常模式进行挖掘。通过实例分析证明该方法能够实现对原始故障数据的精简,有效识别包括信息畸变、保护断路器不正确动作在内的异常信息,从而提高电网故障诊断效率。

关键词(KeyWords)： 电网故障诊断;最大熵隐马尔科夫;信息解析;特征函数;异常模式

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51377054);; 中央高校基本科研业务费专项资金资助项目(JB2015031)~~

作者(Author): 胡江;赵冬梅;张旭;刘志伟;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.0776

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