基于子空间动态系数回归的系统谐波阻抗估计方法

林顺富; 颜昕昱; 戴烨敏; 李东东; 符杨

doi:10.7500/AEPS20190716004

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基于子空间动态系数回归的系统谐波阻抗估计方法

研制与开发 | 更新时间：2025-06-16

- 基于子空间动态系数回归的系统谐波阻抗估计方法
- Estimation Method of System Harmonic Impedance Based on Sub-space Dynamic Coefficient Regression
- 电力系统自动化-方正平台 2020年44卷第12期页码：146-153
- 作者机构：
  
  上海电力大学电气工程学院，上海市 200090
- 作者简介：
  
  林顺富(1983—)，男，通信作者，博士，教授，博士生导师，主要研究方向：电能质量分析及智能电网用户端技术。E-mail：shunfulin@shiep.edu.cn
  颜昕昱(1995—)，男，硕士研究生，主要研究方向：配电网谐波责任划分。E-mail：teufelyan@163.com
  戴烨敏(1995—)，男，硕士研究生，主要研究方向：电力电子装置与电网交互影响。E-mail：Davis_DaiYM@163.com
- 基金信息：
  
  国家自然科学基金资助项目(51977127);上海市科委科技项目(19020500800);上海市人才发展资金资助项目(2018004)
- DOI：10.7500/AEPS20190716004
  中图分类号：
- 收稿日期：2019-07-16，
  
  修回日期：2019-12-12，
  
  网络出版日期：2020-04-16，
  
  纸质出版日期：2020-06-25
- 稿件说明：
移动端阅览
林顺富,颜昕昱,戴烨敏等.基于子空间动态系数回归的系统谐波阻抗估计方法[J].电力系统自动化,2020,44(12):146-153.

LIN Shunfu,YAN Xinyu,DAI Yemin,et al.Estimation Method of System Harmonic Impedance Based on Sub-space Dynamic Coefficient Regression[J].Automation of Electric Power Systems,2020,44(12):146-153.
林顺富,颜昕昱,戴烨敏等.基于子空间动态系数回归的系统谐波阻抗估计方法[J].电力系统自动化,2020,44(12):146-153. DOI： 10.7500/AEPS20190716004.

LIN Shunfu,YAN Xinyu,DAI Yemin,et al.Estimation Method of System Harmonic Impedance Based on Sub-space Dynamic Coefficient Regression[J].Automation of Electric Power Systems,2020,44(12):146-153. DOI： 10.7500/AEPS20190716004.

摘要

系统谐波阻抗的准确估计是实现谐波责任定量划分的关键。新能源并网场景下用户侧谐波阻抗并非远大于系统侧谐波阻抗，现有估计方法精度降低甚至失效。文中提出一种基于子空间分解和动态系数回归的系统谐波阻抗估计方法。通过小波包分解将公共连接点（PCC）处谐波电压与电流的观测信号分解成多个子空间，并根据互信息值筛选出解释变量相关度最弱的子空间，以降低解释变量间相关性对回归分析的影响；考虑到网侧谐波波动会干扰PCC处谐波电压与电流间的相关性，将网侧谐波电压视作动态系数，并通过动态系数回归法求解系统谐波阻抗，以降低网侧谐波电压波动对估计结果的影响。仿真分析的结果表明，相比现有方法

所提方法拥有更好的估计精度与鲁棒性。

Abstract

The accurate estimation of system harmonic impedance is critical to realize the quantitative determination of harmonic responsibility. The customer-side harmonic impedance is no longer much greater than that of the system side in the situation of new energy resources connecting to the grid

which results in accuracy decrease or ineffectiveness of existing estimation methods. This paper proposes an estimation method of system harmonic impedance based on the sub-space decomposition and the dynamic coefficient regression. The observed signals of the harmonic voltage and current at the point of common coupling (PCC) are decomposed into several sub-spaces by the wavelet packet decomposition. The sub-space with the weakest correlation between the explanatory variables is selected according to the mutual information value

which reduces the impact of the correlation between explanatory variables on the regression analysis. Considering that the system harmonic fluctuation will interfere with the correlation between the harmonic voltage and current at PCC

the system harmonic voltage is regarded as a dynamic coefficient. The system harmonic impedance is calculated by the dynamic coefficient regression method

to reduce the impact of harmonic voltage fluctuation on the estimation results. The simulation results show that the proposed method has better estimation accuracy and robustness compared with the existing methods.

关键词

Keywords

references

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