Power system interharmonic estimation method based on auto-regression (AR) model and Kalman filtering

A technology of Kalman filtering and AR model, applied in harmonic reduction devices, AC networks to reduce harmonics/ripples, calculations, etc., can solve problems such as low spectrum analysis performance, low anti-interference ability, and poor real-time performance

Inactive Publication Date: 2011-10-19
HARBIN INST OF TECH
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Problems solved by technology

[0009] The purpose of the present invention is to solve the problems of poor real-time performance of the existing fast Fourier transform method and the low spectral analysis performance and low anti-interference ability of the existing Burg algorithm, and then provide a method based on AR model and Kalman filter Estimation Method of Interharmonics in Power System

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  • Power system interharmonic estimation method based on auto-regression (AR) model and Kalman filtering
  • Power system interharmonic estimation method based on auto-regression (AR) model and Kalman filtering
  • Power system interharmonic estimation method based on auto-regression (AR) model and Kalman filtering

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specific Embodiment approach 1

[0068] Specific Embodiment 1: The method for estimating interharmonics in a power system based on AR model and Kalman filter in this embodiment is realized by the following steps:

[0069] Step A, collect the signal data of the power system, the signal data is as follows:

[0070] Y(n)=[y(1), y(2),...y(N)]

[0071] Where N is the number of signal data;

[0072] Step B, establishing an AR model by collecting the data of the power system signal, and then using the AR model to analyze the power system signal;

[0073] Step B1, the input vector for collecting the power system signal is composed of y(n-1), ..., y(n-p), and the y(n-1), ..., y(n-p) is the sampling sequence of the power system signal, which is composed of These input vectors are associated with p parameters a k Carry out weighted calculations to establish AR model equations, the equations are as follows:

[0074] y ( n ) = Σ ...

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Abstract

The invention discloses a power system interharmonic estimation method based on an auto-regression (AR) model and Kalman filtering, relates to an interharmonic estimation method and aims to solve the problems the conventional fast Fourier transform method has poor real-time property and the conventional Burg algorithm has low spectral analysis performance and low anti-jamming capability. The method comprises the following steps of: A, acquiring signal data of a power system; B, establishing an autoregressive (AR) model according to the acquired signal data of the power system, and analyzing the signal of the power system by utilizing the AR model; C, establishing a state equation and an observational equation; D, determining the order of the AR model according to a final prediction error rule; E, estimating parameters of the AR model on line by utilizing an adaptive Kalman filtering method; and F, performing power spectrum estimation by using the AR model, and substituting the optimal estimated value into an AR model power spectrum density formula for power spectrum estimation. The method is used for estimating the power spectrum of power system interharmonics.

Description

technical field [0001] The invention relates to a method for estimating interharmonics in a power system, in particular to a method for estimating interharmonics in a power system based on an AR model and a Kalman filter. Background technique [0002] With the rapid development of the power system, a large number of power electronic devices, nonlinear fluctuating loads, and interharmonics generated by various frequency conversion speed control devices have increasingly polluted the power system and threatened the safety and economy of various electrical equipment in the power grid. run. Therefore, the analysis of interharmonics in power systems has also become a hot spot widely concerned by scholars at home and abroad, and has very important practical significance. [0003] Commonly used interharmonic detection methods include fast Fourier transform (FFT), eigendecomposition method, artificial neural network model, Burg algorithm and so on. [0004] Fast Fourier Transform ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/01G06F19/00
CPCY02E40/40
Inventor 魏国汪超孙金玮
Owner HARBIN INST OF TECH
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