Reliable Estimate State of Grounding Resistance Based on Extended Kalman Filter

JING Jing; PENG Minfang; ZHOU Bin; LIU Da; LI Xiaofang

doi:10.13296/j.1001-1609.hva.2018.02.027

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Reliable Estimate State of Grounding Resistance Based on Extended Kalman Filter

更新时间：2025-04-26

- Reliable Estimate State of Grounding Resistance Based on Extended Kalman Filter
- High VoltageApparatus Vol. 54, Issue 2, Pages: 166-172+179(2018)
- 作者机构：
  
  湖南大学电气与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2018.02.027
  CLC： TM862
- Published：2018
- 稿件说明：
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[1]荆晶,彭敏放,周斌,刘达,李小方.基于扩展卡尔曼滤波算法的接地电阻状态可靠估计[J].高压电器,2018,54(02):166-172+179.

JING Jing, PENG Minfang, ZHOU Bin, et al. Reliable Estimate State of Grounding Resistance Based on Extended Kalman Filter[J]. High voltageapparatus, 2018, 54(2): 166-172+179.
[1]荆晶,彭敏放,周斌,刘达,李小方.基于扩展卡尔曼滤波算法的接地电阻状态可靠估计[J].高压电器,2018,54(02):166-172+179. DOI： 10.13296/j.1001-1609.hva.2018.02.027.

JING Jing, PENG Minfang, ZHOU Bin, et al. Reliable Estimate State of Grounding Resistance Based on Extended Kalman Filter[J]. High voltageapparatus, 2018, 54(2): 166-172+179. DOI： 10.13296/j.1001-1609.hva.2018.02.027.

摘要

针对目前接地网故障诊断一般只能诊断出严重腐蚀支路或腐蚀断裂支路的缺陷

结合电网络理论和现代信号处理中的扩展卡尔曼滤波算法

提出基于扩展卡尔曼滤波算法的接地网支路电阻状态的可靠估计。根据接地网的拓扑结构

建立状态方程和观测方程

状态方程和观测方程均在估计值处进行Taylor展开

实现线性化

运用算法迭代得到采样时间内支路电阻值的变化趋势及对应电阻变化率。利用Python对实际算例进行仿真

其结果与通过电化学方法检测计算得到的电阻变化率比较

可验证所提方法的准确性。

Abstract

Currently

ground fault diagnosis can only diagnose with severe corrosion branches or corrosion crackingbranches.Ror this shortage

combined with electrical network theory and extended Kalman filtering algorithm inmodern signal processing

this article proposes a reliable estimation for branch resistance state based on extendedKalman filtering algorithm.Depending on the topology of grounding grids

the first step is establishing state equationand observation equation;the second step is carrying them out respectively at an estimated value of the Taylorexpansion in order to realize the linearization. By means of an iterative algorithm

it can obtain the tendency ofbranch resistance value and resistance change rate within the sampling time. Through practical examples usingPython

results compared with the rate of change in resistance calculated by electrochemical detection verify theaccuracy of the proposed method.

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