【摘要】：由于高功率半導(dǎo)體器件的進(jìn)步以及其良好的控制能力，使越來越多的基于電力電子技術(shù)的非線性設(shè)備得到廣泛的應(yīng)用，但這些設(shè)備產(chǎn)生的諧波和間諧波注入到系統(tǒng)中也造成許多嚴(yán)重的問題。因此諧波治理刻不容緩。高精度的諧波分析是電網(wǎng)諧波治理的前提條件�？焖俑道锶~變換（FFT）是諧波分析最有效和最快捷的方法。但FFT需要同步采樣，且存在混疊效應(yīng)、截斷效應(yīng)和柵欄效應(yīng)的影響，這都會影響參數(shù)估計的精度，當(dāng)對間諧波分析的時候，，影響尤為嚴(yán)重。除此之外，F(xiàn)FT的分辨率也很低，如何突破FFT的分辨率極限將是間諧波分析的重要問題。本文針對上述問題進(jìn)行展開，詳細(xì)闡述了如何有效的提高參數(shù)估計的精度和可靠性。 （1）提出了一種考慮頻譜泄露的能量重心法。為了減小能量重心法中頻譜干擾給信號參數(shù)估計帶來的誤差，本文在能量重心法的過程中引入了迭代過程對頻譜幅值進(jìn)行修正。迭代的初值可由能量重心法得到，迭代的過程是在FFT的結(jié)果上不斷減去正頻率和負(fù)頻率的頻譜泄露的值，再重復(fù)進(jìn)行能量重心法，迭代過程的終止取決于定義在時域中迭代誤差。仿真表明，該算法對弱信號有比較好的估計精度，同時迭代次數(shù)也不高，計算代價不大，故是一種很實(shí)用的方法。 （2）提出了一種基于信息論和MUSIC算法的諧波參數(shù)估計方法。首先利用信息論（AIC準(zhǔn)則、MDL準(zhǔn)則），正則相關(guān)技術(shù)等方法來估計正弦成分?jǐn)?shù)。通過仿真分析和比較，在后續(xù)仿真中本文采用MDL準(zhǔn)則來進(jìn)行正弦成分?jǐn)?shù)估計。正確估計正弦成分?jǐn)?shù)之后，本章提出采用空間譜估計中的MUSIC算法進(jìn)行諧波估計。通過對同一種復(fù)雜電力信號與Burg算法進(jìn)行仿真比較，MUSIC算法能夠更準(zhǔn)確的進(jìn)行諧波估計。 （3）提出了一種高精度正弦成分?jǐn)?shù)估計的ESPRIT諧波分析方法。該方法首先利用RD曲線估計信號的頻率成分?jǐn)?shù)，進(jìn)而利用ESPRIT算法估計頻率，幅值和相位。仿真表明，基于該方法的諧波估計方法不僅在短數(shù)據(jù)時具有高精度和高分辨率，而且具有良好魯棒性。
[Abstract]:Due to the progress of high-power semiconductor devices and their good control ability, more and more nonlinear devices based on power electronics technology have been widely used. However, the harmonic and interharmonic injected into the system also cause many serious problems. Therefore, harmonic management is urgent. High precision harmonic analysis is the precondition of harmonic control. Fast Fourier transform (FFT) is the most effective and fast method for harmonic analysis. However, FFT needs synchronous sampling, and there are the effects of aliasing, truncation and fence effect, which will affect the accuracy of parameter estimation, especially when the interharmonic analysis is done. In addition, the resolution of FFT is also very low, how to break through the resolution limit of FFT will be an important problem in interharmonic analysis. In this paper, the above problems are expanded, and how to improve the accuracy and reliability of parameter estimation is discussed in detail. The main results are as follows: (1) an energy center of gravity method considering spectrum leakage is proposed. In order to reduce the error caused by spectral interference in the energy barycenter method, the iterative process is introduced to modify the amplitude of the spectrum in the process of the energy center of gravity method. The initial value of the iteration can be obtained by the energy center of gravity method. The iterative process is to subtract the values of the positive and negative frequency spectrum leakage from the results of the FFT, and then repeat the energy center of gravity method. The termination of the iterative process depends on the iterative error defined in the time domain. Simulation results show that the proposed algorithm has good estimation accuracy for weak signals, low iteration times and low computational cost, so it is a practical method. (2) A harmonic parameter estimation method based on information theory and MUSIC algorithm is proposed. Firstly, the information theory (AIC criterion, MDL criterion) and canonical correlation technique are used to estimate the sinusoidal fraction. Through simulation analysis and comparison, this paper uses MDL criterion to estimate sinusoidal fraction in subsequent simulation. After estimating the sinusoidal fraction correctly, this chapter proposes to use the MUSIC algorithm in spatial spectrum estimation for harmonic estimation. By comparing the same complex power signal with Burg algorithm, the MUSIC algorithm can estimate harmonics more accurately. (3) A ESPRIT harmonic analysis method with high accuracy for sinusoidal fraction estimation is proposed. In this method, the frequency fraction of the signal is estimated by the RD curve, and then the frequency, amplitude and phase are estimated by the ESPRIT algorithm. Simulation results show that the harmonic estimation method based on this method not only has high accuracy and high resolution in short data, but also has good robustness.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM935

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