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利用多源信息的配电系统故障诊断Petri网模型 被引量:5

A Petri net based fault diagnosis model employing information from multiple sources
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摘要 与输电系统相比,配电系统覆盖面更广,包含的元件/设备更多,发生故障的机会也更大。另一方面,配电系统中配置的保护设备不像输电系统那么先进和全面,故障后的警报信息少且未必完整,故障诊断的难度因而未必比输电系统小。这样,在配电系统故障诊断中,充分利用来自多个渠道的信息就更为重要。在此背景下,提出了一种基于Petri网的多源信息配电系统故障诊断模型,可以容纳来自能量管理系统(EMS)、调度管理系统(OMS)、生产管理系统(PMS)、保护信息系统等多方面的信息,并根据一定规则将获取的信息转换成逻辑判据。针对配电系统的不同元件,提出了基于Petri网的故障诊断模型,分析了不同的库所置信度和变迁权重对故障诊断结果的影响;讨论了保护设备误动/拒动、信息漏报/误报对故障诊断的影响并归纳了可能的故障类型,用于评估故障诊断模型的可靠性和容错性。算例测试结果表明了所提出的Petri网故障诊断模型的可行性。 Compared with transmission system,distribution system contains more components/devices,and the possibility of failure is greater.On the other hand,the protection devices in distribution system are generally not as advanced as those in transmission system,and the uploaded alarm information may not be complete,and hence the fault diagnosis in distribution system may even be more difficult than that in transmission system.Thus,it is necessary to make full use of information from multiple sources.Given this background,a Petri net based model is proposed for fault diagnosis in distribution system employing information from multiple sources,including the EMS,PMS/OMS,protection information system.Specifically,all received information is first converted into a logical criterion following certain rules.Petri models for components including buses and lines are next presented,and the impacts of the confidence levels and weights of transitions on fault diagnosis discussed.The impacts of malfunctions of protection devices as well as missing or false alarms on fault diagnosis are examined,and possible fault types summarized for evaluating the reliability of the fault diagnosis model.The proposed Petri net based fault diagnosis model is demonstrated by simulation results of sample power systems.
出处 《华北电力大学学报(自然科学版)》 CAS 北大核心 2014年第6期7-13,共7页 Journal of North China Electric Power University:Natural Science Edition
基金 国家科技支撑计划资助项目(2011BAA07B02) 国网江苏省电力公司科技项目(JS2014002)
关键词 配电系统 故障诊断 PETRI网 多源信息 模型评价 distribution system fault diagnosis Petri net multi-source information model evaluation
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