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Estimation Method of System Harmonic Impedance Based on Sub-space Dynamic Coefficient Regression

College of Electrical Engineering, Shanghai University of Electric Power, Shanghai200090, China

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This work is supported by National Natural Science Foundation of China (No. 51977127), Science and Technology Project of Shanghai Science and Technology Commission (No. 19020500800) and Shanghai Talent Development Fund (No. 2018004).

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    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.

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    表 1 4种不同方法的系统侧5次谐波阻抗估计误差Table 1 Estimation errors of system-side 5th harmonic impedance with four different methods
    表 13 Table 13
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    图1 诺顿等效电路图Fig.1 Norton equivalent circuit diagram
    图2 本文所提估计方法流程图Fig.2 Flow chart of proposed estimation method
    图3 4种不同方法的估计误差分布图Fig.3 Distribution diagrams of estimation errors of four different methods
    图4 a取不同值时谐波阻抗估计误差分析曲线Fig.4 Analysis curves for estimation errors of harmonic impedance with different values of a
    图5 r取不同值时谐波阻抗估计误差分析曲线Fig.5 Analysis curves of estimation errors of harmonic impedance with different values of r
    图 PCC处5次谐波电压与谐波电流测量结果Fig. Measurement results of 5th harmonic voltage and harmonic current at the PCC
    图 仅考虑k时阻抗实部与虚部估计结果的相对误差Fig. Relative errors of the real part and the imaginary part of the impedance considering k only
    图 4种方法谐波阻抗估计结果相对误差分布图Fig. Distribution diagram of relative errors of the estimated results of harmonic impedance
    图 a取不同值的情况下谐波阻抗估计误差分布图Fig. Distribution diagram of estimation errors of the harmonic impedance with different values of a
    图 谐波信号相关系数趋势图Fig. Related coefficient trends of harmonic signals
    图 k 取不同值的情况下估计误差关于 r 的分布图Fig. Distribution diagram of estimation errors with respect to r with different values of k
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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

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  • Received:July 16,2019
  • Revised:December 12,2019
  • Adopted:
  • Online: June 18,2020
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