【作者】 李明；

【导师】 杨洪耕；

【作者基本信息】 四川大学 ， 电力电子与电力传动， 2005， 硕士

【摘要】 随着工业技术的进步与发展,电能质量问题日益突出,越来越受到人们的关注和重视,已经成为电力系统一大重要的研究领域。一方面,随着非线性负荷的不断增加,造成电能质量问题的各种因素不断增长,如电力电子技术的发展及其在工业和交通部门的广泛应用,另一方面,各种复杂的、精密的、对电能质量敏感的用电设备不断普及,人们对电能质量及其可靠性的要求越来越高。 作为电能质量研究中的两个重要内容,即电力系统谐波与电压凹陷,目前,对它们的研究重点已从定量分析转到治理的层面上,即对补偿装置的研究。为向补偿装置提供准确、实时的控制信号,保证良好的补偿效果,优秀的检测算法是必不可少的,因此本文研究了谐波和电压凹陷的检测算法。 本文首先分析了目前常用的谐波与电压凹陷检测算法,通过理论分析与仿真实验逐一指出了现有检测算法存在的不足之处。基于卡尔曼滤波器具有动态实时性强,检测精度高的特点,故可将其用于对谐波和电压凹陷的检测,以期获得更佳的检测效果。然而,传统的卡尔曼滤波器存在以下问题:问题一,因噪声统计特性估计不准确和计算机舍入误差引起的滤波发散现象;问题二,在卡尔曼滤波器达到稳态时,其误差方差阵将饱和使其对信号的突变变得不敏感,问题三,传统的卡尔曼滤波器对滤波参数无自适应能力,不能随着噪声统计特性的改变而调整自身的滤波参数。针对传统卡尔曼滤波器的缺陷,本文提出了基于奇异值分解的自适应卡尔曼滤波。该方法首先利用一个矩阵的奇异值和奇异向量对矩阵元素的摄动反应不敏感,而且对一定的精度误差反应也很小的特点,通过矩阵的奇异值分解有效地抑制了滤波发散现象。然后,通过建立暂态检测函数来判断信号是否发生了突变,若信号发生了突变,就立即将误差方差更多还原

【Abstract】 With the rapid growth of economics, power quality issue has increasingly captured considerable attention from both utility companies and their customers. On one hand, with the increase of nonlinear loads, there are more and more factors that will bring challenge on the power quality, for instance the progress on power electronics appliance and its implementation in industry and transportation companies. On the other hand, people have higher request on the power quality and reliability of power system because more complex, rigid and power quality-sensitive appliance is widely used.Power harmonics and voltage sag are two important matters in power quality research. The research key to them has been from quantities analysis to put them in order now, namely the research to compensation equipment. A good detection way is absolutely necessarily to compensation equipment for getting excellent effect. Thereby, this paper has studied the detection of harmonics and voltage sag.First of all, usual detections of harmonics and voltage sag are analysed in the paper. The deficiency of usual detections has been pointed out one by one through theory analysis and simulation. The kalman Filter can be used to detect harmonics and voltage sag in virtue of fairly high speediness and precision of detection. However, the traditional kalman filter has some deficiencies. Firstly, the filter divergence will happen because of inexact estimation to statistic characteristic of the noise and rounding error of computer. Secondly, when kalman filter has reachedsteady state its error covariance will have a very small stationary value, namely "filter dropping off’. Thirdly, the traditional kalman filter cannot adjust its filter parameters with statistic characteristic of the noise. To overcome the deficiency of kalman filter, an SVD-based adaptive kalman filter is put forward in the paper. The filter restrains the filter divergence by matrix singular value decomposition. The eigenvalues and eigenvectors of the matrix are insensitive to tiny change of matrix element and acceptable error. Then, a transient indication function can be constructed to judge whether abrupt changes of signal has happened. Once a transient has been detected kalman filter reset the value of error covariance matrix to a predefined high level so as to increase the sensitivity of kalman filter and match the changes of the signal. Finally, kalman filter has been made possess strong adaptive ability by improving Sage-Husa algorithm. The validity has been proved through simulation analysis. At the same time its detection of harmonics and voltage sag has excellent performance.更多还原