基于数据驱动的复杂配网故障扰动源定位方法  

Fault Disturbance Source Location Method for Complex Distribution Network Based on Data-driven

作　　者：张永年 赵宝平 米睿煊 丁奎平 王智勇 Zhang Yongnian;Zhao Baoping;Mi Ruixuan;Ding Kuiping;Wang Zhiyong(College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou Gansu 730050,China;State Grid Gansu Electric Power Company Pingliang Power Supply Company,Pingliang Gansu 744000,China)

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050 [2]国网甘肃省电力公司平凉供电公司,甘肃平凉744000

出　　处：《电气自动化》2021年第5期59-61,共3页Electrical Automation

基　　金：国家自然科学基金资助项目(51467009);甘肃省基础研究创新群体项目(18JR3RA133)。

摘　　要：由于在复杂配电网中网络结构复杂,采集数据量过大,现有的故障诊断技术很难快速诊断故障。针对这一问题,提出一种基于数据驱动的复杂配电网故障扰动源定位方法。首先利用基于模块度函数的社区结构分类方法结合数据处理中心位置将复杂配电网络进行分区。然后将每个分区内的故障数据建立增广矩阵,并利用随机矩阵理论中的单环定理进行数据分析,得出各个区域内的数据分析结果,并根据分析结果实现故障扰动源定位。最后,通过IEEE 39节点标准系统进行算例仿真,验证所提方法的有效性和准确性。Due to the complex network structure and large amount of data collected in the complex distribution network, the existing fault diagnosis technology is difficult to quickly diagnose the fault. In order to solve this problem, a data-driven fault source location method for complex distribution network was proposed. Firstly, the complex distribution network was partitioned by using the community structure classification method based on modularity function and the location of data processing center. Then, the fault data in each partition was established as augmented matrix, and the single ring theorem in the random matrix theory was used to analyze the data, and the data analysis results in each region were obtained, and the fault disturbance source location was realized according to the analysis results. Finally, the example simulation was carried out by the IEEE 39 bus standard system. The effectiveness and accuracy of the proposed method were verified.

关 键 词：复杂配电网 社区结构 随机矩阵理论 单环定理 

分 类 号：TM744[电气工程—电力系统及自动化]