Online identification and evaluation algorithm of abnormal disturbance of traction power supply system

被引：0
|
作者：
Yu J. [1 ]
Hu H. [1 ]
Tao H. [1 ]
机构：
[1] School of Electrical Engineering, Southwest Jiaotong University, Chengdu
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2023年 / 43卷 / 08期
基金：
中国国家自然科学基金;
关键词：
abnormal disturbance identification; Hilbert transform; severity evaluation; singular spectrum analysis; TLS-ESPRIT algorithm; traction power supply system;
D O I：
10.16081/j.epae.202212021
中图分类号：
学科分类号：
摘要：
The transient／steady-state overvoltage and overcurrent generated by abnormal electrical disturbances in the traction power supply system have the characteristics of similar features，large frequency separation range，and difficulty in capturing. These characteristics make it difficult to determine the type of disturbance events and identify the key modes and parameters of the disturbance. Therefore，a feature extraction algorithm based on singular spectrum analysis and Hilbert transform is proposed，which realizes the online rapid identification of different abnormal disturbance types. Then the total least squares-estimation of signal parameters via rotational invariance techniques（TLS-ESPRIT） algorithm is improved to accurately evaluate the disturbance modal parameters. According to the characteristics of each disturbance and the key modal parameters of the disturbance，the evaluation index of disturbance severity is defined. The above algorithms are used to identify the simulated data and the measured data. The results show that the proposed algorithms can effectively and quickly identify the type of abnormal disturbance in traction power supply system and further evaluate its severity. © 2023 Electric Power Automation Equipment Press. All rights reserved.
引用
收藏
页码：217 / 224
页数：7
相关论文
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