基于盲源分离理论的闪变和间谐波检测技术研究
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摘要
随着非线性、冲击性负荷等大功率电力电子装置在电力系统中的不断增多,必然产生电压闪变和间谐波干扰,电网被污染,造成电能质量日益下降,影响了人们的日常生活和生产。因此准确检测闪变和间谐波,是评价电能质量的基础,是提高电能质量的前提。目前通常用小波分析法和各种快速傅里叶变换法检测闪变和谐波、间谐波,但易受频谱泄漏和栅栏效应等的影响。为提高检测闪变和谐波、间谐波参数的精度,本文首先研究了用盲源分离算法从产生闪变和谐波、间谐波的畸变电压信号中分离出闪变和谐波、间谐波的波形,再通过计算得到它们的频率;然后研究了分析闪变包络的幅值及间谐波的幅值、相位的粒子群算法,在此基础上研制了验证本文提出的闪变和间谐波检测方法的试验系统,解决了闪变和间谐波检测的若干关键技术问题。论文主要完成的研究工作如下:
研究了如何利用单只电压互感器输出的信号序列构造延迟矩阵,以代替多个传感器输出信号阵列,满足盲源分离的要求并进行了盲源分离,实现了从含有多个频率分量的闪变、间谐波信号中分离出闪变包络及各谐波、间谐波频率分量的波形。
为准确得到闪变的频率和波动值,避免频谱混叠和泄漏等问题,用基于互信息最小化准则的Fast-ICA算法从发生闪变的采样信号中分离出闪变包络波形,通过计算得到闪变的波动值和频率;为提高检测精度,进一步提出了先由盲源分离得到载波波形,计算出载波频率和幅值,然后应用免疫粒子群算法对目标函数进行优化,得到闪变的频率和波动值,此算法与希尔伯特-黄变换法相比,提高了检测精度。选取了适合于闪变包络检测的db24小波,将电压采样信号序列进行分解,在低频带得到闪变包络波形,并将基于互信息最小化准则的快速不动点独立分量分析算法与小波算法进行了比较,结果表明该算法的检测误差小于小波算法。为符合实际工作情况,研究了在含有噪声情况下,用盲源分离算法分离闪变包络的方法。由于噪声和闪变信号、载波信号相互独立,因此用鲁棒预白化方法,降低噪声的影响,将闪变包络波形分离出来,省去了去噪过程,节省了软硬件开销,提高了计算效率。
谐波是电能质量的重要组成部分,为辨识基波、谐波、间谐波的各项参数,提出了基于同时对角化二阶盲辨识算法分离各频率分量波形,通过计算得到具体频率值,用免疫粒子群优化算法辨识基波、各次谐波、间谐波的幅值和相位,结果表明在间谐波频率点处检测精度高于快速傅里叶变换法和Blackman-Harris窗插值快速傅里叶变换算法,尤其是提高了间谐波的相位测量精度。由于免疫粒子群算法避免了早熟现象的发生,本文采用上述算法取得了良好的效果,试验结果证明是间谐波检测的有效方法。
由于难以在电网上进行实验,设计并实现了验证本文提出的电压闪变、间谐波检测方法的试验硬件平台,实现了闪变包络波形的检测及频率、幅值的计算算法;实现了基波、间谐波频率、幅值、相位参数确定算法;完成了电压传感器的标定和测试,评测了算法的有效性和实时性,验证了试验系统的功能。
With the continuous application of large power electronic devices of the non-linear and impact loads, which cause the voltage flicker and interharmonics, the power grid is polluted and its quality is declined. People’s daily life and production is affected. So detecting the flicker and interharmonics accurately is a basis of evaluating power quality, and a premise of improving power quality. Currently wavelet analysis and various fast Fourier transform methods are used to detect flicker, harmonics, and interharmonics. However, these methods are vulnerable to spectrum leakage and grid effect. In order to improve the precision of detecting flicker, harmonics, and interharmonics, some research have done. Firstly, this dissertation researches blind source separation (BSS) algorithm to separate waveform of flicker, harmonics, and interhamonics from input signals and calculate the frequency of flicker and interharmonics. Secondly, this dissertation deeply studies the methods for calculating the amplitude and phase of flicker and interharmonics. Finally, the testing system of flicker and interharmonics has been developed to validate the proposed detection method and resolve some key technologies in flicker and interharmonics detection. The main contributions of this dissertation are as follows:
This dissertation proposes a method of constructing a delay matrix using the output signal sequence of single voltage transformer instead of the multiple sensor output signal arrays. The matrix satisfies the basic requirement of BSS so that each frequency component is separated from flicker, harmonics and interharmonics which contain a number of frequencies.
To accurately obtain the frequency and fluctuation of the flicker and avoid spectrum aliasing and spectrum leakage, This dissertation uses fast independent component analysis (Fast-ICA) based on minimum mutual information algorithm to separate the flicker envelop curve from sampling signals. Then frequency and fluctuation of the flicker is calculated. In order to improve the precision, BSS and particle swarm optimization are selected to detect flicker, and implement the frequency and amplitude calculation of carrier signal and flicker envelope curve respectively. It improves detection precision compared with Hilbert - Huang transform. With the application of db24 wavelet function for decomposing voltage sampling signals, the flicker envelope curve can be separated in low band. Also, Fast-ICA is compared with this db24 wavelet function and the former results show that detection error is lower than wavelet transform. In the noisy case, we research the BSS method to separate the flicker curve. As the noises, flicker signal and carrier signal are independent of each other, the robust pre-whitening method has been used in BSS and the flicker envelope curve is separated smoothly from the signal. This method eliminates the denoising process, lessens the costs of hardware and software and further improves the calculating efficiency.
Harmonic is an important part of power quality. To identify the fundamental and interharmonics parameters, this paper proposes the simultaneous diagonalization second order blind identification algorithm to separate each frequency component. Meanwhile, every frequency value is computed. Then the amplitude and phase are calculated by using the immune particle swarm optimization (IPSO) algorithm. Theexperiments results show that the precision of this method is higher than FFT and Blackman-Harris window function interpolation FFT at interharmonics, especially for the phase precision. IPSO avoids the premature phenomena. This dissertation makes good use of these methods and the precision is also higher. Experiment results approve that it is an effective interharmonics detection method.
The flicker and interharmonics testing hardware platform to validate the proposed voltage flicker and interharmonics detection methods is implemented. It accomplishes the flicker envelope curve detection using the frequency and amplitude calculating algorithm. The fundamental and interharmonics frequency, amplitude and phase calculating algorithm are implemented on this platform, too. The experiments are done including voltage sensor calibration and testing in order to evaluate the reliability and the real-time ability of the algorithm and the function of the testing system.
研究了如何利用单只电压互感器输出的信号序列构造延迟矩阵,以代替多个传感器输出信号阵列,满足盲源分离的要求并进行了盲源分离,实现了从含有多个频率分量的闪变、间谐波信号中分离出闪变包络及各谐波、间谐波频率分量的波形。
为准确得到闪变的频率和波动值,避免频谱混叠和泄漏等问题,用基于互信息最小化准则的Fast-ICA算法从发生闪变的采样信号中分离出闪变包络波形,通过计算得到闪变的波动值和频率;为提高检测精度,进一步提出了先由盲源分离得到载波波形,计算出载波频率和幅值,然后应用免疫粒子群算法对目标函数进行优化,得到闪变的频率和波动值,此算法与希尔伯特-黄变换法相比,提高了检测精度。选取了适合于闪变包络检测的db24小波,将电压采样信号序列进行分解,在低频带得到闪变包络波形,并将基于互信息最小化准则的快速不动点独立分量分析算法与小波算法进行了比较,结果表明该算法的检测误差小于小波算法。为符合实际工作情况,研究了在含有噪声情况下,用盲源分离算法分离闪变包络的方法。由于噪声和闪变信号、载波信号相互独立,因此用鲁棒预白化方法,降低噪声的影响,将闪变包络波形分离出来,省去了去噪过程,节省了软硬件开销,提高了计算效率。
谐波是电能质量的重要组成部分,为辨识基波、谐波、间谐波的各项参数,提出了基于同时对角化二阶盲辨识算法分离各频率分量波形,通过计算得到具体频率值,用免疫粒子群优化算法辨识基波、各次谐波、间谐波的幅值和相位,结果表明在间谐波频率点处检测精度高于快速傅里叶变换法和Blackman-Harris窗插值快速傅里叶变换算法,尤其是提高了间谐波的相位测量精度。由于免疫粒子群算法避免了早熟现象的发生,本文采用上述算法取得了良好的效果,试验结果证明是间谐波检测的有效方法。
由于难以在电网上进行实验,设计并实现了验证本文提出的电压闪变、间谐波检测方法的试验硬件平台,实现了闪变包络波形的检测及频率、幅值的计算算法;实现了基波、间谐波频率、幅值、相位参数确定算法;完成了电压传感器的标定和测试,评测了算法的有效性和实时性,验证了试验系统的功能。
With the continuous application of large power electronic devices of the non-linear and impact loads, which cause the voltage flicker and interharmonics, the power grid is polluted and its quality is declined. People’s daily life and production is affected. So detecting the flicker and interharmonics accurately is a basis of evaluating power quality, and a premise of improving power quality. Currently wavelet analysis and various fast Fourier transform methods are used to detect flicker, harmonics, and interharmonics. However, these methods are vulnerable to spectrum leakage and grid effect. In order to improve the precision of detecting flicker, harmonics, and interharmonics, some research have done. Firstly, this dissertation researches blind source separation (BSS) algorithm to separate waveform of flicker, harmonics, and interhamonics from input signals and calculate the frequency of flicker and interharmonics. Secondly, this dissertation deeply studies the methods for calculating the amplitude and phase of flicker and interharmonics. Finally, the testing system of flicker and interharmonics has been developed to validate the proposed detection method and resolve some key technologies in flicker and interharmonics detection. The main contributions of this dissertation are as follows:
This dissertation proposes a method of constructing a delay matrix using the output signal sequence of single voltage transformer instead of the multiple sensor output signal arrays. The matrix satisfies the basic requirement of BSS so that each frequency component is separated from flicker, harmonics and interharmonics which contain a number of frequencies.
To accurately obtain the frequency and fluctuation of the flicker and avoid spectrum aliasing and spectrum leakage, This dissertation uses fast independent component analysis (Fast-ICA) based on minimum mutual information algorithm to separate the flicker envelop curve from sampling signals. Then frequency and fluctuation of the flicker is calculated. In order to improve the precision, BSS and particle swarm optimization are selected to detect flicker, and implement the frequency and amplitude calculation of carrier signal and flicker envelope curve respectively. It improves detection precision compared with Hilbert - Huang transform. With the application of db24 wavelet function for decomposing voltage sampling signals, the flicker envelope curve can be separated in low band. Also, Fast-ICA is compared with this db24 wavelet function and the former results show that detection error is lower than wavelet transform. In the noisy case, we research the BSS method to separate the flicker curve. As the noises, flicker signal and carrier signal are independent of each other, the robust pre-whitening method has been used in BSS and the flicker envelope curve is separated smoothly from the signal. This method eliminates the denoising process, lessens the costs of hardware and software and further improves the calculating efficiency.
Harmonic is an important part of power quality. To identify the fundamental and interharmonics parameters, this paper proposes the simultaneous diagonalization second order blind identification algorithm to separate each frequency component. Meanwhile, every frequency value is computed. Then the amplitude and phase are calculated by using the immune particle swarm optimization (IPSO) algorithm. Theexperiments results show that the precision of this method is higher than FFT and Blackman-Harris window function interpolation FFT at interharmonics, especially for the phase precision. IPSO avoids the premature phenomena. This dissertation makes good use of these methods and the precision is also higher. Experiment results approve that it is an effective interharmonics detection method.
The flicker and interharmonics testing hardware platform to validate the proposed voltage flicker and interharmonics detection methods is implemented. It accomplishes the flicker envelope curve detection using the frequency and amplitude calculating algorithm. The fundamental and interharmonics frequency, amplitude and phase calculating algorithm are implemented on this platform, too. The experiments are done including voltage sensor calibration and testing in order to evaluate the reliability and the real-time ability of the algorithm and the function of the testing system.
引文
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