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省级配电自动化主站的停电信息资源池功能设计
引用本文:冷华,钱玉麟,朱吉然,唐海国,张伟伟,张海文. 省级配电自动化主站的停电信息资源池功能设计[J]. 电力系统自动化, 2020, 44(13): 150-156
作者姓名:冷华  钱玉麟  朱吉然  唐海国  张伟伟  张海文
作者单位:1.湖南大学电气与信息工程学院,湖南省长沙市 410082;2.南瑞集团有限公司(国网电力科学研究院有限公司),江苏省南京市 211106;3.国网湖南省电力有限公司电力科学研究院,湖南省长沙市 410004;4.国网湖南省电力有限公司永州供电分公司,湖南省永州市 425000;5.国网湖南省电力有限公司,湖南省长沙市 410003
基金项目:国家电网公司科技项目(5216A019000R)。
摘    要:各地配电自动化建设尚处于大规模试点阶段,很多区域的故障信息感知和定位手段有限,不同性质的停电事件信息又来源于多个业务系统,在条件有限的情况下实现停电事件精准分析的需求尤为迫切。文中结合电力公司的停电管理实际业务流程,设计停电信息资源池功能,综合分析变电站、馈线、台区、用户多层主网和配电网数据,在分层分级研判基础上建立信号可信度模型。结合DS证据理论算法融合分析,多维度灵活地挖掘分析停电事件,提高故障点定位的容错性,满足在差异化场景下构建可靠的结构化停电信息资源池实现数据的共享发布。

关 键 词:停电分析  配电自动化  大数据  故障定位  DS证据理论
收稿时间:2019-05-29
修稿时间:2019-11-07

Function Design of Power Outage Information Resource Pool for Provincial Distribution Automation Main Station
LENG Hu,QIAN Yulin,ZHU Jiran,TANG Haiguo,ZHANG Weiwei,ZHANG Haiwen. Function Design of Power Outage Information Resource Pool for Provincial Distribution Automation Main Station[J]. Automation of Electric Power Systems, 2020, 44(13): 150-156
Authors:LENG Hu  QIAN Yulin  ZHU Jiran  TANG Haiguo  ZHANG Weiwei  ZHANG Haiwen
Affiliation:1.College of Electrical and Information Engineering, Hunan University, Changsha 410082, China;2.NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China;3.Electric Power Research Institute of State Grid Hunan Electric Power Company Limited, Changsha 410004, China;4.Yongzhou Electric Power Supply Company of State Grid Hunan Electric Power Company Limited, Yongzhou 425000, China;5.State Grid Hunan Electric Power Company Limited, Changsha 410003, China
Abstract:The construction of distribution automation is still in a large-scale pilot stage. In many areas, the means of fault information perception and location are limited. The information of different power outage events come from multiple business systems. It is particularly urgent to achieve accurate analysis of power outage events under limited conditions. Combining with the actual business process of power outage management of the electric utilities, this paper designs the function of power outage information resource pool, comprehensively analyzes the data of multi-layer main network and distribution network of substations, feeders, distribution transformer areas and users, and establishes the signal credibility model on the basis of hierarchical study and judgment. Combining fusion analysis of DS evidence theory algorithm, multi-dimensional flexible mining and analysis of power outage events, the fault tolerance of fault location is improved, and a reliable structured power outage information resource pool is built to achieve data sharing and publishing in different scenarios.
Keywords:power outage analysis  distribution automation  big data  fault location  DS evidence theory
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