College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
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).
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 that the existing estimation methods have low accuracy or become ineffective. 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 connection (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 out 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.
LIN Shunfu,YAN Xinyu,DAI Yemin,et al.Estimation Method of System Harmonic Impedance Based on Sub-space Dynamic Coefficient Regression[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190716004.