基于小波变换与现代谱估计的谐波检测方法研究
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摘要
随着社会现代化进程的不断发展,电力系统遍及各行各业,再加上大量的非线性元器件的投入使用,电网中的谐波问题越来越复杂。由以往电力系统发生的故障经验可以看出,部分是由谐波造成的。因此,为了改善和提高电能的质量,必须要采取有效的技术手段。能够准确的检测故障发生的位置以及故障发生的原因。针对这样的问题,在已有的研究成果基础之上,对电力系统谐波的检测与调控方法作进一步的研究。
傅立叶变换最早应用于谐波的检测也最为经典。但是随着电力系统变得越来越复杂,加入的随机有害噪声严重影响了傅立叶变换检测的效果,而且傅立叶变换的方法不能兼顾频域和时域。再加上其运算量比较大,这就导致它不能满足实时性检测的要求。针对这一情况,选择了小波变换的谐波检测方法。通过大量的仿真实验证明,对于绝大多数的谐波都能有较好的检测效果。尤其是其在消除噪声方面的显著作用。
由于小波变换具有良好的时域与频域局部化特性,这也是它能在现代谐波检测中得到广泛应用的原因。而现代谱估计中的Prony算法理论又具有较高的频率分辨率,能分离出各频率分量。利用这种方法的谐波检测并且通过Matlab仿真可以发现,在无噪声干扰的情况下,Prony算法具有很好的检测效果。但是在加入噪声后的仿真可以发现其受噪声的影响非常大。在经典Prony算法的基础上,针对实际环境对传统的Prony算法进行改进,该方法不仅大大减少了运算量,而且可以在低噪声的环境下无需消噪就能够精确的分析。
针对上述出现的结果以及前面提到的小波变换在信号去噪方面的独特之处,因此,运用综合小波变换与现代谱估计相结合的谐波检测的方法。通过弥补两者的不足,取两者的优点。通过反复的仿真验证,得出这样的思想是满足要求的。而且有着很好的检测效果。
本文主要就是针对以上所讲述的思想进行仿真验证。通过仿真证明这种思想的可行的。使得谐波检测变得更加简单、高效、快捷。
Along with the social modernization development, power system throughout all walks of life, plus a lot of nonlinear components in use, harmonic problems become more and more complex. Power system fault by previous experience can be seen, in part by caused by harmonics. Therefore, in order to improve and enhance the quality of electric energy, must take effective technical means. To be able to accurately detect the fault location and fault cause. In view of such problems, the existing research results foundation, on the power system harmonic detection and control method for further study.
Fourier transform was first applied to harmonic detection is the most classic. But with the development of power system is becoming more and more complex, add random harmful noise seriously affects the Fu Liye transform detection effect, and Fu Liye transform method can not take into account the frequency domain and time domain. Plus the amount of calculation is relatively large, which leads to it can't meet the need of real-time detection. In view of this situation, choice of wavelet transform harmonic detection method. The simulation results prove that, for the vast majority of the harmonic can have good detection effect. Especially the significant role in the elimination of noise.
Because wavelet transform has good localization characteristics of time domain and frequency domain, it can in the modern harmonic detection is widely used in the cause of. Modern spectral estimation algorithm of Prony in theory but also has higher frequency resolution, to isolate the various frequency components. By using the method of harmonic detection and through the Matlab simulation can be found, in no noise case, Prony algorithm has good detection effect. But in the adding noise simulation can be found under the influence of the noise is very big. In the classical Prony algorithm based on, in view of the actual environment of the traditional Prony algorithm, this method not only reduces the amount of computation, but also in low noise environment without de-noising can accurate analysis.
According to the result and the previously mentioned wavelet transform in signal denoising is unique, therefore, comprehensively by using wavelet transform and modern spectrum estimation by combining the harmonic detection method. Through making up for the shortcomings of both, with the advantages of both. Through repeated simulation, draw the idea is to meet the requirements of the. And a good detection effect.
This article is in view of the above described the thought is validated by simulation. The simulation results show that this kind of thought and feasible. The harmonic detection becomes more simple, efficient, fast.
傅立叶变换最早应用于谐波的检测也最为经典。但是随着电力系统变得越来越复杂,加入的随机有害噪声严重影响了傅立叶变换检测的效果,而且傅立叶变换的方法不能兼顾频域和时域。再加上其运算量比较大,这就导致它不能满足实时性检测的要求。针对这一情况,选择了小波变换的谐波检测方法。通过大量的仿真实验证明,对于绝大多数的谐波都能有较好的检测效果。尤其是其在消除噪声方面的显著作用。
由于小波变换具有良好的时域与频域局部化特性,这也是它能在现代谐波检测中得到广泛应用的原因。而现代谱估计中的Prony算法理论又具有较高的频率分辨率,能分离出各频率分量。利用这种方法的谐波检测并且通过Matlab仿真可以发现,在无噪声干扰的情况下,Prony算法具有很好的检测效果。但是在加入噪声后的仿真可以发现其受噪声的影响非常大。在经典Prony算法的基础上,针对实际环境对传统的Prony算法进行改进,该方法不仅大大减少了运算量,而且可以在低噪声的环境下无需消噪就能够精确的分析。
针对上述出现的结果以及前面提到的小波变换在信号去噪方面的独特之处,因此,运用综合小波变换与现代谱估计相结合的谐波检测的方法。通过弥补两者的不足,取两者的优点。通过反复的仿真验证,得出这样的思想是满足要求的。而且有着很好的检测效果。
本文主要就是针对以上所讲述的思想进行仿真验证。通过仿真证明这种思想的可行的。使得谐波检测变得更加简单、高效、快捷。
Along with the social modernization development, power system throughout all walks of life, plus a lot of nonlinear components in use, harmonic problems become more and more complex. Power system fault by previous experience can be seen, in part by caused by harmonics. Therefore, in order to improve and enhance the quality of electric energy, must take effective technical means. To be able to accurately detect the fault location and fault cause. In view of such problems, the existing research results foundation, on the power system harmonic detection and control method for further study.
Fourier transform was first applied to harmonic detection is the most classic. But with the development of power system is becoming more and more complex, add random harmful noise seriously affects the Fu Liye transform detection effect, and Fu Liye transform method can not take into account the frequency domain and time domain. Plus the amount of calculation is relatively large, which leads to it can't meet the need of real-time detection. In view of this situation, choice of wavelet transform harmonic detection method. The simulation results prove that, for the vast majority of the harmonic can have good detection effect. Especially the significant role in the elimination of noise.
Because wavelet transform has good localization characteristics of time domain and frequency domain, it can in the modern harmonic detection is widely used in the cause of. Modern spectral estimation algorithm of Prony in theory but also has higher frequency resolution, to isolate the various frequency components. By using the method of harmonic detection and through the Matlab simulation can be found, in no noise case, Prony algorithm has good detection effect. But in the adding noise simulation can be found under the influence of the noise is very big. In the classical Prony algorithm based on, in view of the actual environment of the traditional Prony algorithm, this method not only reduces the amount of computation, but also in low noise environment without de-noising can accurate analysis.
According to the result and the previously mentioned wavelet transform in signal denoising is unique, therefore, comprehensively by using wavelet transform and modern spectrum estimation by combining the harmonic detection method. Through making up for the shortcomings of both, with the advantages of both. Through repeated simulation, draw the idea is to meet the requirements of the. And a good detection effect.
This article is in view of the above described the thought is validated by simulation. The simulation results show that this kind of thought and feasible. The harmonic detection becomes more simple, efficient, fast.
引文
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