首页|高压用户电气系统智能终端拓扑识别方法研究

高压用户电气系统智能终端拓扑识别方法研究

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随着电网环境越来越复杂,运行过程中的不确定性持续增大、拓扑结构不断发生改变导致难以准确识别故障.为了提高高压用户供用电系统的拓扑结构识别准确性,提出了一种基于智能终端测量数据的高压用户电气系统智能终端拓扑识别方法.利用电气智能终端的通信地址对各级交换机子节点进行关联,采集电气智能终端节点数据.根据聚类算法,确定各分支电能数据的父子关系特征.创新性地通过数据聚类分析方法得到系统中各级馈线节点的隶属关系,实现高压用户电气系统拓扑识别.在三种情境下进行拓扑识别效果测试.测试结果表明,该方法准确识别出了同一台区不同情况下的三种拓扑结构,能够有效利用测量数据准确识别配电系统的拓扑结构.
Research on Topology Identification Method of Intelligent Terminals for High-Voltage Consumer Electrical Systems
As the grid environment is becomes increasingly complex,and the uncertainty in the operation process continues to increase,and the topology is constantly changing leading to difficulties in accurately recognizing faults.To improve the accuracy of topology identification of high-voltage consumers power supply and use systems,an intelligent terminal topology identification method for high-voltage consumers electrical systems based on intelligent terminal measurement data is proposed.The communication address of the electrical intelligent terminal is utilized to correlate the switch sub-nodes at all levels,and the electrical intelligent terminal node data is collected.According to the clustering algorithm,the parent-child relationship characteristics of the electrical energy data of each branch are determined.Innovatively,the affiliation of feeder nodes at all levels in the system is obtained through the data clustering analysis method to realize the topology identification of high-voltage consumer electrical system.The effect of topology identification is tested in three scenarios.The test results show that the method accurately recognizes three topologies under different situations in the same station area and can effectively use the measurement data to accurately identify the topology of the distribution system.

Electrical systemsHigh-voltage consumerIntelligent terminalCluster analysisTopology identificationSwitch

杨恒、袁金斗、张腾、薛溟枫、毛晓波、潘明明

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国家电网公司,北京 100031

中国电力科学研究院有限公司,北京 100192

国网江苏省电力有限公司,江苏 南京 210000

国网江苏省电力有限公司无锡供电分公司,江苏 无锡 214000

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电气系统 高压用户 智能终端 聚类分析 拓扑识别 交换机

国家电网科技基金

5400-202118164A-0-0-00

2024

自动化仪表
中国仪器仪表学会 上海工业自动化仪表研究院

自动化仪表

CSTPCD
影响因子:0.655
ISSN:1000-0380
年,卷(期):2024.45(5)
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