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Abstract
Accurately determining power consumer harmonic contribution determination is an effective method to solve power quality disputes and alleviate harmonic pollution of power grids. This paper proposes a multi-harmonic sources harmonic contribution determination algorithm based on data filtering and cluster analysis. Aiming at the problem of background harmonic fluctuation, this paper uses the cross-approximation entropy (CAE) algorithm to filter the effective data segments of the harmonic voltage and current at the point of common coupling (PCC) to avoid the interference caused by background harmonics. For the problem of harmonic impedance changes of system, using the density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm to detect the harmonic impedance changes of the system. The harmonic contribution under different system harmonic impedance is calculated based on the data of each class cluster. The accuracy of the proposed method is improved compared with existing methods. The experimental analysis demonstrates the effectiveness and superiority of the algorithm.
Highlights
With a large number of power electronic devices connected to the power grid, the harmonic pollution caused by it has become one of the prominent problems affecting the power quality of the power grid
Aiming at the problem of background harmonic fluctuation, this paper firstly applies the cross-approximation entropy (CAE) algorithm to select the effective harmonic voltage and current data segments at the point of common coupling (PCC) to avoid the interference caused by background harmonics
The 5th harmonic voltage and current waveform of the PCC are shown in the Fig.9(a), (b): Firstly, the 5th harmonic data of IPCC and UPCC are filtered, and the retained data is analyzed by density-based spatial clustering of applications with noise (DBSCAN) clustering
Summary
With a large number of power electronic devices connected to the power grid, the harmonic pollution caused by it has become one of the prominent problems affecting the power quality of the power grid. Compared to the fluctuation method [14], [15], the most widely used in practice is linear regression The principle of this method is to calculate the regression coefficient of the corresponding equation according to the voltage and current measurement values at the PCC in the harmonic equivalent circuit and obtain the system harmonic impedance parameters. This paper uses the CAE algorithm to filter out the data segments with large background harmonic fluctuations, so as to improve the accuracy of the result. It can be known from (3) that determination of the harmonic contribution should be based on the fact that the system harmonic impedance remains unchanged.
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