湖南电力 ›› 2023, Vol. 43 ›› Issue (4): 133-138.doi: 10.3969/j.issn.1008-0198.2023.04.020

• 故障与分析 • 上一篇    

基于预充电模型的直流支撑电容器状态辨识方法研究

田睿1, 刘维可2, 伍珣3   

  1. 1.国网湖南省电力有限公司超高压变电公司,湖南 长沙 410004;
    2.国网湖南省电力有限公司电力科学研究院,湖南 长沙 410208;
    3.中南大学交通运输工程学院,湖南 长沙 410075
  • 收稿日期:2023-06-12 出版日期:2023-08-25 发布日期:2023-09-07
  • 通信作者: 伍珣(1993),男,讲师,通信作者,主要从事电气设备状态监测与故障诊断研究。
  • 作者简介:田睿(1992),女,工程师,主要从事电气设备状态监测与故障诊断研究。
  • 基金资助:
    湖南省自然科学基金项目(2023JJ40750)

A Condition Estimation Method for DC-link Capacitors Based on Pre-charging Model

TIAN Rui1, LIU Weike2, WU Xun3   

  1. 1. State Grid Hunan Extra High Voltage Substation Company, Changsha 410004, China;
    2. State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410208, China;
    3. School of Transportation and Engineering, Central South University, Changsha 410075, China
  • Received:2023-06-12 Online:2023-08-25 Published:2023-09-07

摘要: 直流支撑电容器是变流系统能量缓存的关键部件,广泛应用于机车牵引、航空航天、风力发电、光伏发电等领域。在恶劣工作环境下,直流支撑电容器性能退化,失效率上升,极易损坏。现有的电容器状态辨识方法容易受传感器测量噪声影响,导致电容量辨识结果与实际值相差甚远。针对上述问题,提出一种基于预充电过程的电容器状态辨识方法,通过构建预充电模型,得到电容量与电压信号的映射关系并最大程度削减测量噪声影响;在此基础上,采用递推辅助变量最小二乘法对预充电模型的参数进行估计,从而得到准确的电容器电容量辨识结果。验证结果表明,该方法能够有效抵御测量噪声干扰,在信号采样频率大于500 Hz时具有较好的辨识效果;当采样频率达到1 kHz时,电容量辨识误差为0.569%。

关键词: 电容器, 电容量, 预充电, 状态辨识

Abstract: DC-link capacitors are key components for energy buffering in converter systems and are widely used in fields such as locomotive traction, aerospace, wind power generation and photovoltaic power generation. In harsh working environments, the performance of DC-link capacitors deteriorates, the failure rate increases, and they are easily damaged. Currently, the existing methods for state identifying of capacitors are easily affected by sensor measurement noise, resulting in a significant difference between the capacitance identification results and the actual values. To solve these problems, this paper proposes a capacitor state identification method based on the pre-charging process. By constructing the pre-charging model, the mapping relationship between capacitance and voltage signal is obtained, and the influence of measurement noise is minimized. Then, the recursive auxiliary variable least square method is used to estimate the parameters of the pre-charging model, so as to obtain the accurate capacitor capacity identification results. The verification results show that this method can effectively resist the interference of measurement noise, and has good identification effect when the signal sampling frequency is greater than 500 Hz. The capacitance identification error is 0.569% when the sampling frequency reaches 1 kHz.

Key words: capacitor, capacitance, pre-charging, state identification

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