基于RS-IA数据挖掘的配电网故障定位模型

发布时间：2018-01-07 21:35

本文关键词：基于RS-IA数据挖掘的配电网故障定位模型　出处：《电力自动化设备》2017年05期 　论文类型：期刊论文

【摘要】：针对配电网故障定位的相关性分析过程中,由于馈线终端单元(FTU)运行环境较恶劣、元器件受损或信息丢失等导致故障信息变异的问题,提出基于粗糙集(RS)理论和免疫算法(IA)相结合的数据挖掘配电网故障定位相关性分析模型。首先,借助RS理论提取领域知识,将给定变异故障模式集合转换成RS中的决策表;然后,利用IA进行决策表的属性约简,并挖掘出该问题中输入矢量(条件属性)与输出矢量(决策属性)的相互关联性规则;最后,将该数据挖掘方法用于处理FTU实时输入信息的畸变,根据各分段开关的电流越限信息序列判断各段线路故障状态,实现配电网的故障定位,并通过算例验证了所提模型的可行性和有效性。
[Abstract]:In the process of correlation analysis of distribution network fault location, due to the poor operation environment of feeder terminal unit (FTU), the damage of components and components or the loss of information, the fault information is changed. A data mining fault location correlation analysis model based on rough set RS (RS) theory and immune algorithm (IAA) is proposed. Firstly, domain knowledge is extracted by means of RS theory. The set of given fault modes is transformed into a decision table in RS. Then, we use IA to reduce the attribute of decision table, and find out the correlation rules of input vector (conditional attribute) and output vector (decision attribute) in this problem. Finally, the data mining method is used to deal with the distortion of the real-time input information of FTU. According to the information sequence of the current limit of each segment switch, the fault state of each segment is judged, and the fault location of the distribution network is realized. The feasibility and validity of the proposed model are verified by an example.
【作者单位】：天津大学电气自动化与信息工程学院;
【基金】：国家自然科学基金-民航联合研究基金资助项目(U1533126) 国家电网公司总部科技项目(配电自动化系统精益化运维关键技术研究与开发)~~
【分类号】：TM76
【正文快照】： 0引言配电网故障定位是配电自动化的重要功能之一。当配电网实际出现故障后,通过故障定位功能可快速找出故障发生的区域,为隔离故障和尽快恢复用户供电提供有效指导,对提高供电可靠性具有重要意义。配电网故障定位一般包括故障告警、故障相关性分析和故障精确定位3个步骤。目

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