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基于逻辑节点的分布式馈线自动化拓扑识别
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山东理工大学电气与电子工程学院,山东省淄博市 255000

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基金项目:

国家重点研发计划资助项目(2016YFB0900600);国家电网有限公司资助项目(52094017000W);山东省重点研发计划资助项目(2019GGX103019)


Topology Identification of Distributed Feeder Automation Based on Logical Nodes
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College of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China

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This work is supported by National Key R&D Program of China (No. 2016YFB0900600), State Grid Corporation of China (No. 52094017000W), and Key Research and Development Plan of Shandong (No. 2019GGX103019).

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    摘要:

    分布式馈线自动化(FA)需要馈线实时拓扑信息实现故障定位、隔离以及非故障区段的供电恢复。文中分析了分布式FA应用对馈线实时拓扑的需求,基于IEC 61850建模方法新建了单元拓扑逻辑节点和拓扑片节点来表达馈线拓扑。使用配电终端配置的拓扑片信息和当前的开关设备状态信息,基于深度优先搜索可实现馈线实时拓扑的识别,满足分布式FA应用需求,算例验证了方法有效性。

    Abstract:

    Distributed feeder automation (FA) requires real-time topology information of feeder to realize fault location, isolation, and power restoration in non-faulty sections. This paper analyzes the requirements of feeder real-time topology for the application of distributed FA. Based on the modeling method for IEC 61850,new unit topology logic nodes and topology slice nodes are created to express the feeder topology. The topology information configured of the STU and the status information of the current switch device are applied. The real-time topology identification of feeder based on depth-first search is realized to meet the application requirements of distributed FA. The validity of the proposed method is verified through case study.

    图1 典型的配电网线路Fig.1 Typical distribution network lines
    图2 故障后的配电网线路Fig.2 Distribution network lines after a failure
    图3 配电网线路拓扑示意图Fig.3 Schematic diagram of distribution network line topology
    图4 RTPM1的数据框格式Fig.4 Data frame format of RTPM1
    图5 RTCN3的数据框格式Fig.5 Data frame format of RTCN3
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引用本文

王宗晖,陈羽,徐丙垠,等.基于逻辑节点的分布式馈线自动化拓扑识别[J/OL].电力系统自动化,http://doi.org/10.7500/AEPS20190718006.
WANG Zonghui,CHEN Yu,XU BingYin,et al.Topology Identification of Distributed Feeder Automation Based on Logical Nodes[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190718006.

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  • 收稿日期:2019-07-18
  • 最后修改日期:2020-04-09
  • 录用日期:2020-01-06
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