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Harmonic source responsibility division method based on cross-approximate entropy data screening

A technology of mutual approximate entropy and data screening, which is applied in spectral analysis/Fourier analysis, instruments, measuring devices, etc., and can solve problems such as large estimation error and poor fit.

Active Publication Date: 2020-09-22
STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST +3
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the interference of background harmonics is a key factor affecting the accuracy of non-interventional harmonic estimation, but the traditional linear regression method is poor in fitting when the background harmonic voltage fluctuates, and in practice the background harmonic voltage often changes. And it is random, so the traditional linear regression method has a large estimation error

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  • Harmonic source responsibility division method based on cross-approximate entropy data screening
  • Harmonic source responsibility division method based on cross-approximate entropy data screening
  • Harmonic source responsibility division method based on cross-approximate entropy data screening

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0080] Embodiment 1: Basic explanation of the division of harmonic responsibilities; the division of harmonic responsibilities in power systems can be represented by Norton equivalent circuits, as follows figure 1 As shown in , the harmonic voltage and current values ​​at the common connection point are simultaneously contributed by the harmonic sources on the system side and the user side. where I ch is the equivalent harmonic source on the user side, I sh is the equivalent harmonic source on the system side, Z ch is the user-side equivalent harmonic impedance, Z sh is the equivalent harmonic impedance of the system side, and h represents the harmonic order.

[0081] According to the superposition theorem, the figure 1 It is converted into two parts superimposed on the system side and the user side, such as figure 2 Shown:

[0082] In the picture I pcc-s is the equivalent harmonic source I on the system side s Contributing Harmonic Current, V s Contribute harmonic v...

Embodiment 2

[0099] Embodiment 2: The principle of mutual approximation entropy is explained; From the above-mentioned principle, if the influence of background harmonics is excluded, V pcc with I pcc The waveform pattern is consistent. The accuracy of the system harmonic impedance calculated from this will be higher. Therefore, in order to filter out V pcc with I pcc For data segments with similar waveform trends, this paper introduces the concept of mutual approximation entropy, and uses the method of waveform segment matching to convert V pcc with I pcc Similar waveform data segments are retained, and dissimilar data segments are eliminated to achieve the purpose of eliminating background harmonic interference.

[0100] Aiming at the problems that traditional entropy requires a large amount of sampled data, is sensitive to noise, and is not easy to converge, Steven M. Pincus proposed Approximate Entropy (ApEn) in the 1990s from the perspective of measuring the complexity of time se...

Embodiment 3

[0116] Example 3: Principle of M-estimation robust regression method; the traditional linear regression method uses the least squares method for calculation, and its principle is to minimize the sum of squares of residual errors. When there are outliers in the original data, the calculation of the least squares method will accommodate the remote data, which increases the calculation error, so the traditional linear regression method lacks robustness. In this paper, M-estimated robust regression is used to eliminate the influence of outliers on the method [18]. The following is an example of linear regression calculation. Known measured data (x i ,y i )(i=1,2,...,n), if the linear relationship is y=ax+b, the coefficients a and b of the equation can be calculated by the least square method.

[0117] From the above description, we can see that the residual e i The objective function of can be expressed as:

[0118]

[0119] The traditional least squares method is to estim...

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Abstract

The invention aims at solving various simulation conditions of background harmonic voltage fluctuation. Analyzing and comparing the advantages and disadvantages of the method and the traditional linear regression method, the invention provides a harmonic source responsibility division method based on CAE data screening, and the method comprises the steps: firstly dividing collected actual measurement data into a plurality of sections, carrying out the cross-approximation entropy calculation of the actual measurement harmonic voltage and current data of each section, and reserving the sectionsmeeting the requirements of a CAE threshold, so as to achieve the purpose of eliminating background harmonic interference; and then performing regression calculation on the reserved data by utilizingan M estimation robust regression method to avoid the influence of abnormal values on regression calculation to the greatest extent and obtain the harmonic impedance of the system, thereby realizing accurate harmonic responsibility division.

Description

technical field [0001] The invention relates to a harmonic source responsibility division method based on mutual approximation entropy data screening, and belongs to the technical field of power quality control. Background technique [0002] At present, with a large number of power electronic equipment connected to the grid, the harmonic pollution caused by it has become one of the outstanding problems of the power quality of the grid. In order to ensure the power supply reliability of the power grid and ensure the quality of power supply, it is imperative to punish the electricity users who cause the grid harmonics to exceed the standard. Accurate measurement of users' harmonic emission levels and clear division of harmonic responsibilities are the prerequisites for reasonable rewards and punishments for power users. The estimation result of user harmonic emission level is obtained from the calculation of system equivalent harmonic impedance, so the key to evaluating user ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R23/16G01R31/08
CPCG01R23/16G01R31/088Y02E40/40
Inventor 史明明张宸宇唐伟佳张国江付慧李双伟范忠
Owner STATE GRID JIANGSU ELECTRIC POWER CO ELECTRIC POWER RES INST
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