复杂电力谐波分析方法研究

发布时间：2019-02-22 16:15

【摘要】：由于高功率半导体器件的进步以及其良好的控制能力，使越来越多的基于电力电子技术的非线性设备得到广泛的应用，但这些设备产生的谐波和间谐波注入到系统中也造成许多严重的问题。因此谐波治理刻不容缓。高精度的谐波分析是电网谐波治理的前提条件。快速傅里叶变换（FFT）是谐波分析最有效和最快捷的方法。但FFT需要同步采样，且存在混叠效应、截断效应和栅栏效应的影响，这都会影响参数估计的精度，当对间谐波分析的时候，，影响尤为严重。除此之外，FFT的分辨率也很低，如何突破FFT的分辨率极限将是间谐波分析的重要问题。本文针对上述问题进行展开，详细阐述了如何有效的提高参数估计的精度和可靠性。（1）提出了一种考虑频谱泄露的能量重心法。为了减小能量重心法中频谱干扰给信号参数估计带来的误差，本文在能量重心法的过程中引入了迭代过程对频谱幅值进行修正。迭代的初值可由能量重心法得到，迭代的过程是在FFT的结果上不断减去正频率和负频率的频谱泄露的值，再重复进行能量重心法，迭代过程的终止取决于定义在时域中迭代误差。仿真表明，该算法对弱信号有比较好的估计精度，同时迭代次数也不高，计算代价不大，故是一种很实用的方法。（2）提出了一种基于信息论和MUSIC算法的谐波参数估计方法。首先利用信息论（AIC准则、MDL准则），正则相关技术等方法来估计正弦成分数。通过仿真分析和比较，在后续仿真中本文采用MDL准则来进行正弦成分数估计。正确估计正弦成分数之后，本章提出采用空间谱估计中的MUSIC算法进行谐波估计。通过对同一种复杂电力信号与Burg算法进行仿真比较，MUSIC算法能够更准确的进行谐波估计。（3）提出了一种高精度正弦成分数估计的ESPRIT谐波分析方法。该方法首先利用RD曲线估计信号的频率成分数，进而利用ESPRIT算法估计频率，幅值和相位。仿真表明，基于该方法的谐波估计方法不仅在短数据时具有高精度和高分辨率，而且具有良好鲁棒性。
[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.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM935

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