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A Cat Swarm Algorithm Optimized Least Mean Square Adaptive Harmonic Detection Method

A technology of harmonic detection and cat swarm algorithm, applied in the field of electric power, can solve the problems of low harmonic detection accuracy and sensitive initial value, and achieve the effects of improving accuracy and real-time performance, reducing steady-state error, and improving power quality.

Active Publication Date: 2021-07-20
NANCHANG UNIV
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Problems solved by technology

For example, the least mean square (LMS) algorithm is applicable to both three-phase systems and single-phase systems, but the LMS algorithm, as the most widely used adaptive filtering algorithm, has the obvious disadvantage of being sensitive to the initial value, resulting in relatively low harmonic detection accuracy. Low

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  • A Cat Swarm Algorithm Optimized Least Mean Square Adaptive Harmonic Detection Method
  • A Cat Swarm Algorithm Optimized Least Mean Square Adaptive Harmonic Detection Method
  • A Cat Swarm Algorithm Optimized Least Mean Square Adaptive Harmonic Detection Method

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[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0040] like Figure 1-6 As shown, one embodiment of the present invention discloses a cat swarm algorithm optimization minimum root mean square adaptive harmonic detection method, comprising the following steps:

[0041] S1: current signal sampling: for periodic load current i with harmonics L (t) Sampling to obtain the load current i corresponding to the current sampling moment L (t) discrete value i L (n);

[0042] S2: given an input reference signal where A is the amplitude, f is the frequency, is the phase, corresponding value range: -2≤A≤2, 48≤f≤52, Correspondingly, the discrete signal x(n) of x(t) is obtained;

[0043] S3: Obtain the estimated value y(n) of the fundamental current through the LMS algorithm, namely: y(n)=x(n)*w T (n); wherein w(n) is the weight...

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Abstract

The invention discloses a minimum root mean square adaptive harmonic detection method optimized by a cat swarm algorithm, which relates to the field of electric power technology. On the basis of the harmonic detection of the traditional variable step size root mean square (LMS) algorithm, the cat swarm algorithm ( CSO) optimizes it, solves the problems of the traditional method being sensitive to the initial value and poor detection accuracy, and realizes the real-time detection of harmonics in the load current. Through this method, the detection accuracy of harmonics is higher and the convergence speed is faster. Fast; at the same time, it is of great significance to effectively control harmonics and improve power quality.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a minimum root mean square adaptive harmonic detection method optimized by a cat group algorithm. Background technique [0002] In recent years, with the use of a large number of nonlinear power electronic devices in the field of electric power technology, a large number of harmonics have seriously reduced the power quality of users and the stability of equipment operation. Effective harmonic compensation methods have been adopted to solve power grid harmonics. The problem of wave pollution is urgent, and the active power filter (APF) that can dynamically compensate harmonics has been widely used. Among them, the harmonic detection link is a key part of APF, and the accuracy and effectiveness of detection directly affect the harmonics. Therefore, it is more and more important to study and improve the algorithm of harmonic real-time detection. Currently widely used harmon...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R23/165
CPCG01R23/165
Inventor 聂晓华万良
Owner NANCHANG UNIV
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