CN108318761A - Wind power generating set power quality detection method based on compressed sensing - Google Patents
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Abstract
Description
技术领域technical field
本发明涉及智能电网领域，更具体的涉及基于压缩感知的风力发电机组电能质量检测方法。The invention relates to the field of smart grids, and in particular to a method for detecting the power quality of wind power generating sets based on compressed sensing.
背景技术Background technique
传统的电能质量数据采集分析系统是基于奈奎斯特采样定理实现的，该过程包括信号采集—压缩—存储/传输—信号重构—分析处理，要想无失真的恢复原始信号，采样频率必须是原始信号最高频率的两倍或者以上。The traditional power quality data acquisition and analysis system is based on the Nyquist sampling theorem. The process includes signal acquisition-compression-storage/transmission-signal reconstruction-analysis and processing. In order to restore the original signal without distortion, the sampling frequency must be It is twice or more than the highest frequency of the original signal.
基于奈奎斯特采样定理的电能质量采样处理系统主要存在两方面缺点，一方面为了满足Nyquist采样定理，要求采样设备必须保持较高采样速率，进而增加了硬件设备的成本；另一方面，为了存储和计算采集到的大量的电能质量信号数据，需要相当大的存储空间和计算能力，增加了数据存储和计算的压力。The power quality sampling processing system based on the Nyquist sampling theorem mainly has two shortcomings. On the one hand, in order to satisfy the Nyquist sampling theorem, the sampling equipment must maintain a high sampling rate, which increases the cost of the hardware equipment; on the other hand, in order to Storing and calculating a large amount of collected power quality signal data requires considerable storage space and computing power, which increases the pressure on data storage and calculation.
因此，现有对风力发电机组电能质量检测的方法存在数据采集量大和计算复杂度高，导致对硬件系统要求高的问题。Therefore, the existing methods for detecting the power quality of wind turbines have the problems of large data collection and high computational complexity, which lead to high requirements for hardware systems.
发明内容Contents of the invention
本发明实施例提供基于压缩感知的风力发电机组电能质量检测方法，用以解决现有技术中数据采集量大和计算复杂度高，导致对硬件系统要求高的问题。Embodiments of the present invention provide a method for detecting power quality of wind power generators based on compressed sensing, which is used to solve the problem in the prior art that the large amount of data collection and high computational complexity lead to high requirements on the hardware system.
本发明实施例提供基于压缩感知的风力发电机组电能质量检测方法，包括：步骤1、采集风力发电机组工作状态下的电压闪变信号；The embodiment of the present invention provides a method for detecting the power quality of a wind power generating set based on compressed sensing, comprising: step 1, collecting a voltage flicker signal under a working state of the wind generating set;
步骤2、将所述电压闪变信号通过稀疏表示得到稀疏信号；Step 2, the voltage flicker signal is sparsely represented to obtain a sparse signal;
步骤3、将所述稀疏信号采用稀疏随机测量矩阵进行压缩采样，得到压缩采样后的信号；Step 3, performing compressed sampling on the sparse signal using a sparse random measurement matrix to obtain a compressed sampled signal;
步骤4、将所述压缩采样后的信号采用OMP算法进行重构；Step 4, reconstructing the compressed and sampled signal using the OMP algorithm;
步骤5、计算重构信号的短时闪变严重程度，并检测重构信号闪变包络。Step 5. Calculate the short-term flicker severity of the reconstructed signal, and detect the flicker envelope of the reconstructed signal.
较佳地，所述风力发电机组工作状态下的电压闪变信号为：Preferably, the voltage flicker signal in the working state of the wind power generating set is:
其中，公式(1)中：N为闪变信号的总数，A为电压的幅值，mi是第i项闪变包络的调制度，fi是第i项闪变包络的频率，是第i项闪变包络的相角。Among them, in the formula (1): N is the total number of flicker signals, A is the amplitude of the voltage, m i is the modulation degree of the i-th flicker envelope, f i is the frequency of the i-th flicker envelope, is the phase angle of the i-th flicker envelope.
较佳地，所述将所述电压闪变信号通过稀疏表示得到稀疏信号包括：选择傅里叶变换作为稀疏基矩阵将所述电压闪变信号进行稀疏表示。Preferably, the sparse representation of the voltage flicker signal to obtain a sparse signal includes: selecting Fourier transform as a sparse basis matrix to perform sparse representation of the voltage flicker signal.
较佳地，将所述稀疏信号采用稀疏随机测量矩阵进行压缩采样，得到压缩采样后的信号包括：Preferably, the sparse signal is subjected to compressed sampling using a sparse random measurement matrix, and the obtained compressed-sampled signal includes:
将所述采用稀疏随机测量矩阵乘以所述稀疏信号得到压缩采样后的信号。Multiplying the sparse random measurement matrix by the sparse signal to obtain a compressed sampled signal.
较佳地，所述计算重构信号的短时闪变严重程度，包括：采用以下公式(2)计算重构信号的短时闪变严重程度：Preferably, the calculation of the short-term flicker severity of the reconstructed signal includes: calculating the short-term flicker severity of the reconstructed signal using the following formula (2):
其中，公式(2)中，P0.1、P1、P3、P10、P50五个参数分别表示十分钟之内瞬时闪变视感度S(t)超过0.1％、1％、3％、10％、50％时间的觉察单位值。Among them, in formula (2), the five parameters P 0.1 , P 1 , P 3 , P 10 , and P 50 respectively indicate that the instantaneous flicker sensitivity S(t) exceeds 0.1%, 1%, 3%, and Perception unit value for 10%, 50% of the time.
较佳地，所述检测重构信号闪变包络包括：Preferably, the detection and reconstruction signal flicker envelope includes:
采用Teager能量算子提取出重构信号的瞬时包络和瞬时频率；Using the Teager energy operator to extract the instantaneous envelope and instantaneous frequency of the reconstructed signal;
其中，重构信号的瞬时包络的提取采用如下公式为(3)；重构信号的瞬时频率的提取采用如下公式为(4)和(5)；Wherein, the extraction of the instantaneous envelope of the reconstructed signal adopts the following formula as (3); the extraction of the instantaneous frequency of the reconstructed signal adopts the following formulas as (4) and (5);
其中，公式(3)中，a(n)为瞬时包络，y(n)为重构信号，y1(n)＝y(n)-y(n-1)，ψd[y(n)]表示重构信号y(n)的能量算子；Among them, in formula (3), a(n) is the instantaneous envelope, y(n) is the reconstructed signal, y1(n)=y(n)-y(n-1), ψ d [y(n) ] represents the energy operator of the reconstructed signal y(n);
瞬时频率计算公式为：The formula for calculating the instantaneous frequency is:
其中，公式(4)中，ω(n)为瞬时角频率；Among them, in formula (4), ω(n) is the instantaneous angular frequency;
其中，公式(5)中，f(n)为瞬时频率。Wherein, in formula (5), f(n) is the instantaneous frequency.
本发明实施例中通过将压缩感知理论，应用到风力发电机组电能质量采样检测领域，突破了传统的奈奎斯特采样定理，将采样和压缩同时进行，可大大减少采样数据量，缩短采样时间，降低对风力发电机组电能质量信号采样检测硬件系统的要求，便于数据存储和传输；且采用的稀疏随机测量矩阵对风力发电机组电能质量信号观测压缩处理效果比采用高斯随机矩阵和贝努力矩阵的计算复杂度低，且易于实现，也能降低对风力发电机组电能质量信号采样检测硬件系统的要求。In the embodiment of the present invention, by applying the theory of compressed sensing to the field of sampling and detection of power quality of wind power generating units, it breaks through the traditional Nyquist sampling theorem, and performs sampling and compression at the same time, which can greatly reduce the amount of sampling data and shorten the sampling time , reducing the requirements for the sampling and detection hardware system of the power quality signal of the wind turbine, which is convenient for data storage and transmission; and the sparse random measurement matrix adopted is better than that of Gaussian random matrix and Bernoulli matrix for the observation and compression processing of the power quality signal of the wind turbine The calculation complexity is low, and it is easy to implement, and can also reduce the requirements for the sampling and detection hardware system of the power quality signal of the wind power generating set.
附图说明Description of drawings
图1为本发明实施例提供的基于压缩感知的风力发电机组电能质量检测方法的流程示意图；Fig. 1 is a schematic flow chart of a method for detecting power quality of a wind power generating set based on compressed sensing provided by an embodiment of the present invention;
图2为本发明实施例提供的传统信号获取和处理过程和基于压缩感知理论的信号获取和处理过程对比图；Fig. 2 is a comparison diagram of the traditional signal acquisition and processing process and the signal acquisition and processing process based on compressed sensing theory provided by the embodiment of the present invention;
图3为本发明实施例提供的电压闪变信号波形图；3 is a voltage flicker signal waveform diagram provided by an embodiment of the present invention;
图4为本发明实施例提供的电压闪变信号频谱图；Fig. 4 is the spectrum diagram of the voltage flicker signal provided by the embodiment of the present invention;
图5为本发明实施例提供的电压闪变信号和重构信号对比图；FIG. 5 is a comparison diagram of a voltage flicker signal and a reconstructed signal provided by an embodiment of the present invention;
图6为本发明实施例提供的电压闪变信号瞬时闪变视感度图；Fig. 6 is a voltage flicker signal transient flicker visual sensitivity diagram provided by an embodiment of the present invention;
图7为本发明实施例提供的重构信号的瞬时闪变视感度图；Fig. 7 is the instantaneous flicker visual sensitivity diagram of the reconstructed signal provided by the embodiment of the present invention;
图8为本发明实施例提供的闪变包络随时间变化的波形和检测误差结果图。FIG. 8 is a diagram of the waveform of the flicker envelope changing with time and the detection error results provided by the embodiment of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
本发明实施例提供的基于压缩感知的风力发电机组电能质量检测方法的流程示意图，如图1所示，该方法包括：The embodiment of the present invention provides a schematic flow diagram of a method for detecting power quality of a wind turbine based on compressed sensing, as shown in FIG. 1 , the method includes:
步骤1、采集风力发电机组工作状态下的电压闪变信号。Step 1. Collect the voltage flicker signal in the working state of the wind power generating set.
其中，该风力发电机组工作状态下的电压闪变信号为：Among them, the voltage flicker signal in the working state of the wind turbine is:
式中：N为闪变信号的总数,A为电压的幅值，mi是第i项闪变包络的调制度，fi是第i项闪变包络的频率，是第i项闪变包络的相角。In the formula: N is the total number of flicker signals, A is the amplitude of the voltage, m i is the modulation degree of the i-th flicker envelope, f i is the frequency of the i-th flicker envelope, is the phase angle of the i-th flicker envelope.
步骤2、将该电压闪变信号通过稀疏表示得到稀疏信号。Step 2. Obtain a sparse signal through sparse representation of the voltage flicker signal.
应用压缩感知理论的前提是信号本身具有稀疏性或者在某个变换域内具有稀疏性，即假设信号f∈RN×1的长度为N，信号本身或者经过某种变换后只含有K个非零值者其绝对值远远大于剩余数值，且K<<N，则我们可以认为信号f是稀疏信号，它的稀疏度为K。自然界中，大多数信号本身都不是严格意义上的稀疏信号，但在某些域内是稀疏信号，风力发电机组电能质量信号也是如此。为了满足该前提条件，需将风力发电机组电能质量信号进行稀疏表示，本文采用的稀疏基矩阵ψ∈RN×N是傅里叶变换，稀疏向量为x∈RN×1，即：The premise of applying compressed sensing theory is that the signal itself has sparsity or has sparsity in a certain transformation domain, that is, assuming that the length of the signal f∈R N×1 is N, the signal itself or after some transformation contains only K non-zero value whose absolute value is far greater than the remaining value, and K<<N, then we can consider the signal f to be a sparse signal, and its sparsity is K. In nature, most signals themselves are not sparse signals in the strict sense, but they are sparse signals in some domains, and the same is true for wind turbine power quality signals. In order to meet this prerequisite, the power quality signal of the wind turbine needs to be represented sparsely. The sparse base matrix ψ∈R N×N used in this paper is Fourier transform, and the sparse vector is x∈R N×1 , namely:
f＝ψx、 (2)f=ψx, (2)
步骤3、将该稀疏信号采用稀疏随机测量矩阵进行压缩采样，得到压缩采样后的信号。Step 3. The sparse signal is subjected to compressed sampling by using a sparse random measurement matrix to obtain a compressed-sampled signal.
其中，稀疏随机测量矩阵φ，实现信满足RIP准则，实现稀疏信号从高维到低维的投影，即实现压缩，且保证原始信号在降维过程中重要的信息不丢失。将信号投影至一个和稀疏变换基ψ高度不相关的测量矩阵φ∈RM×N上，得到长度为M的观测信号u。该过程数学表达式为：Among them, the sparse random measurement matrix φ, the realization signal satisfies the RIP criterion, realizes the projection of the sparse signal from high-dimensional to low-dimensional, that is, realizes compression, and ensures that important information of the original signal is not lost during the dimensionality reduction process. The signal is projected onto a measurement matrix φ∈R M×N that is highly uncorrelated with the sparse transformation base ψ, and an observation signal u of length M is obtained. The mathematical expression of the process is:
式中称之为感知矩阵或传感矩阵。In the formula Call it the perception matrix or sensory matrix.
本文使用的测量矩阵是稀疏随机测量矩阵，较其它测量矩阵相比，在实际应用中，稀疏随机测量矩阵容易实现和保存，经过仿真实验证明，针对风力发电机组电能质量信号，其重构效果比应用广泛的高斯随机测量矩阵和贝努力矩阵重构效果要好。The measurement matrix used in this paper is a sparse random measurement matrix. Compared with other measurement matrices, in practical applications, the sparse random measurement matrix is easy to realize and save. Simulation experiments have proved that the reconstruction effect is better than that of wind turbine power quality signals. The widely used Gaussian random measurement matrix and Bernoulli matrix reconstruction effect is better.
步骤4、将该压缩采样后的信号采用OMP算法进行重构。Step 4. The compressed and sampled signal is reconstructed using the OMP algorithm.
其中，重构的过程可看作是解压缩过程，即用重构算法从低维的信号数据中解压缩出原本的高维信号。目前应用的的重构算法主要有两大类：贪婪算法、凸优化算法。贪婪算法主要包括：匹配追踪算法(MP)、正交匹配追踪算法(OMP)等各种基于匹配追踪的改进算法。凸优化算法包括：基追踪(BP)、内点法、梯度投影方法(GPSR)等。本文采用OMP算法实现信号的重构，该算法相对而言计算量较小，速度快，重构信号效率高。Among them, the reconstruction process can be regarded as a decompression process, that is, the original high-dimensional signal is decompressed from the low-dimensional signal data by a reconstruction algorithm. There are two main types of reconstruction algorithms currently used: greedy algorithms and convex optimization algorithms. Greedy algorithms mainly include: matching pursuit algorithm (MP), orthogonal matching pursuit algorithm (OMP) and other improved algorithms based on matching pursuit. Convex optimization algorithms include: basis pursuit (BP), interior point method, gradient projection method (GPSR), etc. In this paper, the OMP algorithm is used to realize the reconstruction of the signal. The algorithm is relatively small in calculation, fast in speed, and highly efficient in reconstructing the signal.
步骤5、计算重构信号的短时闪变严重程度，并检测重构信号闪变包络。Step 5. Calculate the short-term flicker severity of the reconstructed signal, and detect the flicker envelope of the reconstructed signal.
其中，该计算重构信号的短时闪变严重程度，包括：采用以下公式(2)计算重构信号的短时闪变严重程度：Wherein, the calculation of the short-term flicker severity of the reconstructed signal includes: using the following formula (2) to calculate the short-term flicker severity of the reconstructed signal:
其中，公式(2)中，P0.1、P1、P3、P10、P50五个参数分别表示十分钟之内瞬时闪变视感度S(t)超过0.1％、1％、3％、10％、50％时间的觉察单位值。Among them, in formula (2), the five parameters P 0.1 , P 1 , P 3 , P 10 , and P 50 respectively indicate that the instantaneous flicker sensitivity S(t) exceeds 0.1%, 1%, 3%, and Perception unit value for 10%, 50% of the time.
另外，计算得到的Pst与原始信号计算得到的Pst和Pst理论值进行对比，检验误差是否在标准循序的范围内，未超过5％，则符合测量标准，说明将压缩感知理论应用到风力发电机组电能质量测量领域是可行的。In addition, the calculated P st is compared with the P st calculated from the original signal and the theoretical value of P st to check whether the error is within the range of the standard sequence, and if it does not exceed 5%, it meets the measurement standard, indicating that the compressed sensing theory is applied to The field of power quality measurement for wind turbines is feasible.
再者，该检测重构信号闪变包络包括：采用Teager能量算子提取出重构信号的瞬时包络和瞬时频率；Furthermore, the detection of the flicker envelope of the reconstructed signal includes: using a Teager energy operator to extract the instantaneous envelope and instantaneous frequency of the reconstructed signal;
其中，重构信号的瞬时包络的提取采用如下公式为(5)；重构信号的瞬时频率的提取采用如下公式为(6)和(7)；Wherein, the extraction of the instantaneous envelope of the reconstructed signal adopts the following formula as (5); the extraction of the instantaneous frequency of the reconstructed signal adopts the following formulas as (6) and (7);
其中，公式(5)中，a(n)为瞬时包络，y(n)为重构信号，y1(n)＝y(n)-y(n-1)，ψd[y(n)]表示重构信号y(n)的能量算子。Among them, in formula (5), a(n) is the instantaneous envelope, y(n) is the reconstructed signal, y1(n)=y(n)-y(n-1), ψ d [y(n) ] represents the energy operator of the reconstructed signal y(n).
瞬时频率计算公式为：The formula for calculating the instantaneous frequency is:
其中，公式(6)中，ω(n)为瞬时角频率。Among them, in formula (6), ω(n) is the instantaneous angular frequency.
其中，公式(7)中，f(n)为瞬时频率。Among them, in formula (7), f(n) is the instantaneous frequency.
本发明实施例中，将传统信号获取和处理过程和基于压缩感知理论的信号获取和处理过程对比图2所示，从图2中本发明的方法将数据采样和压缩两过程合二为一，减少采样数据量，缩短采样时间，降低对风力发电机组电能质量信号采样检测硬件系统的要求，便于数据存储和传输，同时能提高信号处理的效率，降低信号处理的成本。有效弥补了传统电能质量信号采集处理系统中的不足。In the embodiment of the present invention, the traditional signal acquisition and processing process is compared with the signal acquisition and processing process based on compressed sensing theory as shown in Figure 2. From Figure 2, the method of the present invention combines the two processes of data sampling and compression into one, Reduce the amount of sampling data, shorten the sampling time, reduce the requirements for the hardware system of wind turbine power quality signal sampling and detection, facilitate data storage and transmission, and at the same time improve the efficiency of signal processing and reduce the cost of signal processing. It effectively makes up for the deficiencies in the traditional power quality signal acquisition and processing system.
本发明实施例中，以单一频率电压闪变信号为例，应用压缩感知理论进行压缩采样及重构，并计算短时闪变严重程度：In the embodiment of the present invention, taking a single-frequency voltage flicker signal as an example, compressive sensing theory is used for compressed sampling and reconstruction, and the severity of short-term flicker is calculated:
单一频率电压闪变信号的表达式为：The expression of single frequency voltage flicker signal is:
上式中，取工频载波幅值ω0＝2πf0，取工频载波频率f0＝50Hz，取初相角取闪变包络的调制度mi＝0.125，取闪变包络的频率fi＝8.8Hz，取闪变包络的相角得到如下图3所示波形。In the above formula, take the power frequency carrier amplitude ω 0 ＝2πf 0 , take the power frequency carrier frequency f 0 ＝50Hz, take the initial phase angle Take the modulation degree of the flicker envelope m i =0.125, take the frequency f i =8.8Hz of the flicker envelope, and take the phase angle of the flicker envelope The waveform shown in Figure 3 below is obtained.
根据稀疏信号的定义以及波形图可知，时域中正常电压信号本身不是稀疏信号，为了满足应用压缩感知理论的前提条件，必须通过变换域使得信号满足稀疏性，将电压闪变信号进行傅里叶变换，电压闪变信号的频域波形如图4所示。According to the definition of the sparse signal and the waveform diagram, the normal voltage signal itself in the time domain is not a sparse signal. In order to meet the preconditions of applying the compressive sensing theory, the signal must satisfy the sparsity through the transformation domain, and the voltage flicker signal is Fourier Transform, the frequency domain waveform of the voltage flicker signal is shown in Figure 4.
从图4中明显得出，电压闪变信号在频域是稀疏信号，由此，选择傅里叶变换作为稀疏基矩阵将风力发电机组电能质量信号进行稀疏表示。It is obvious from Figure 4 that the voltage flicker signal is a sparse signal in the frequency domain. Therefore, the Fourier transform is selected as the sparse base matrix to represent the power quality signal of the wind turbine generator sparsely.
本发明实施例中，电压闪变信号选择了工频载波幅值为工频载波频率为50Hz，初相角为0的正弦波作为载波信号，闪变包络的调制度为0.125，调制频率为8.8Hz，初相角为0，采样频率为800Hz，采样时间为10s，可知实际采样点数为8000个。本次仿真选择的观测值个数为64个，选择傅里叶变换作为稀疏基矩阵，通过对高斯随机测量矩阵、贝努力矩阵和稀疏随机测量矩阵研究，分析应用三种不同测量矩阵观测信号,经过仿真实验证明，稀疏随机测量矩阵针对风力发电机组电能质量信号，其重构效果比应用广泛的高斯随机测量矩阵和贝努力矩阵重构效果要好。In the embodiment of the present invention, the amplitude of the power frequency carrier is selected as the voltage flicker signal to be The carrier frequency of the power frequency is 50Hz, the sine wave with the initial phase angle of 0 is used as the carrier signal, the modulation degree of the flicker envelope is 0.125, the modulation frequency is 8.8Hz, the initial phase angle is 0, the sampling frequency is 800Hz, and the sampling time is 10s , it can be seen that the actual number of sampling points is 8000. The number of observations selected in this simulation is 64, and Fourier transform is selected as the sparse base matrix. Through the study of Gaussian random measurement matrix, Bernoulli matrix and sparse random measurement matrix, three different measurement matrix observation signals are analyzed and applied. Simulation experiments show that the reconstruction effect of the sparse random measurement matrix for the power quality signal of wind turbines is better than that of the widely used Gaussian random measurement matrix and Bernoulli matrix.
最后应用稀疏随机测量矩阵作为测量矩阵实现稀疏信号从高维到低维的投影，最后通过OMP算法实现正常电压信号的重构。重构效果如图5所示。Finally, the sparse random measurement matrix is used as the measurement matrix to realize the projection of the sparse signal from high-dimensional to low-dimensional, and finally the normal voltage signal is reconstructed by the OMP algorithm. The reconstruction effect is shown in Figure 5.
其中，为了避免实验结果的随机性和偶然性，对不同的测量矩阵仿真实验20次，计算重构信号的均方根误差的平均值，计算结果如表1所示，可见，稀疏随机测量矩阵效果最后好。可以直接对重构的信号做进一步分析研究，不会带来干扰。Among them, in order to avoid the randomness and contingency of the experimental results, different measurement matrix simulation experiments were performed 20 times, and the average value of the root mean square error of the reconstructed signal was calculated. The calculation results are shown in Table 1. It can be seen that the effect of sparse random measurement matrix Finally good. The reconstructed signal can be further analyzed and studied directly without interference.
表1应用不同测量矩阵的重构误差Table 1. Reconstruction errors using different measurement matrices
应用IEC标准推荐的方法计算原始电压闪变信号和应用稀疏随机矩阵作为测量矩阵并重构的电压闪变信号的短时闪变严重程度，验证是否符合标准规定。Apply the method recommended by the IEC standard to calculate the short-term flicker severity of the original voltage flicker signal and the reconstructed voltage flicker signal using a sparse random matrix as the measurement matrix, and verify whether it complies with the standard.
经过计算得到闪变包络调制度为0.125，调制频率为8.8Hz，初相角为0的电压闪变信号和应用压缩感知理论采样重构的电压闪变信号的短时闪变严重程度Pst均为0.7241，理论值为0.714，误差为1.4201％，未超过标准中规定的5％，符合要求。After calculation, the flicker envelope modulation degree is 0.125, the modulation frequency is 8.8Hz, the voltage flicker signal with an initial phase angle of 0 and the short-term flicker severity P st Both are 0.7241, the theoretical value is 0.714, and the error is 1.4201%, which is not more than 5% specified in the standard and meets the requirements.
若应用奈奎斯特采样定理进行采样，因为原始信号的最高频率为50Hz，所以采样率至少为100Hz，则奈奎斯特采样定理所需要的采样点数为1000个，而本文通过观测得到的64个点即可实现信号重构。If the Nyquist sampling theorem is used for sampling, because the highest frequency of the original signal is 50Hz, the sampling rate is at least 100Hz, then the number of sampling points required by the Nyquist sampling theorem is 1000, and the 64 obtained by observation in this paper The signal can be reconstructed at one point.
通过对比可知，应用压缩感知理论可以实现在采样点数低于奈奎斯特采样点数的情况下准确的重构信号，选择傅里叶变换作为稀疏基矩阵，用稀疏随机测量矩阵实现信号高维到低维的投影，并通过OMP算法重构信号，效果良好，经过验证，符合IEC标准。Through comparison, it can be seen that the application of compressed sensing theory can realize accurate signal reconstruction when the number of sampling points is lower than the number of Nyquist sampling points. Fourier transform is selected as the sparse basis matrix, and the sparse random measurement matrix is used to realize the signal high-dimensional to Low-dimensional projection, and signal reconstruction through OMP algorithm, the effect is good, and it has been verified to meet the IEC standard.
图6为本发明实施例提供的电压闪变信号瞬时闪变视感度图；图7为本发明实施例提供的重构信号的瞬时闪变视感度图；将电压闪变信号和重构信号瞬时闪变视感度数据保存，然后调用依据公式(4)提前编好的统计程序，计算得到闪变包络调制度为0.125，调制频率为8.8Hz，初相角为0的电压闪变信号和应用压缩感知理论采样重构的电压闪变信号的短时闪变严重程度Pst均为0.7241，理论值为0.714，误差为1.4201％，未超过标准中规定的5％，符合要求。Fig. 6 is the instantaneous flicker visual sensitivity diagram of the voltage flicker signal provided by the embodiment of the present invention; Fig. 7 is the instantaneous flicker visual sensitivity diagram of the reconstructed signal provided by the embodiment of the present invention; the voltage flicker signal and the reconstructed signal instantaneous Save the flicker visual sensitivity data, and then call the statistical program compiled in advance according to the formula (4), calculate the flicker envelope modulation degree of 0.125, the modulation frequency of 8.8Hz, the initial phase angle of 0 voltage flicker signal and its application The short-term flicker severity P st of the voltage flicker signal reconstructed by compressive sensing theory sampling and reconstruction is 0.7241, the theoretical value is 0.714, and the error is 1.4201%, which does not exceed the 5% specified in the standard and meets the requirements.
若应用奈奎斯特采样定理进行采样，因为原始信号的最高频率为50Hz，所以采样率至少为100Hz，则奈奎斯特采样定理所需要的采样点数为1000个，而本文通过观测得到的64个点即可实现信号重构。If the Nyquist sampling theorem is used for sampling, because the highest frequency of the original signal is 50Hz, the sampling rate is at least 100Hz, then the number of sampling points required by the Nyquist sampling theorem is 1000, and the 64 obtained by observation in this paper The signal can be reconstructed at one point.
通过对比可知，应用压缩感知理论可以实现在采样点数低于奈奎斯特采样点数的情况下准确的重构信号，选择傅里叶变换作为稀疏基矩阵，用稀疏随机测量矩阵实现信号高维到低维的投影，并通过OMP算法重构信号，效果良好，经过验证，符合IEC标准。Through comparison, it can be seen that the application of compressed sensing theory can realize accurate signal reconstruction when the number of sampling points is lower than the number of Nyquist sampling points. Fourier transform is selected as the sparse basis matrix, and the sparse random measurement matrix is used to realize the signal high-dimensional to Low-dimensional projection, and signal reconstruction through OMP algorithm, the effect is good, and it has been verified to meet the IEC standard.
本发明实施例应用Teager能量算子检测重构信号闪变包络The embodiment of the present invention uses the Teager energy operator to detect and reconstruct the flicker envelope of the signal
根据IEC61000-4-15标准设置闪变电压参数，加入单一频率全部时间电压闪变信号表达式为：Set the flicker voltage parameters according to the IEC61000-4-15 standard, add a single frequency and the expression of the voltage flicker signal for all time is:
在正常电压全部时间段加入闪变信号，闪变电压包络的调制度为0.125，闪变包络的频率为8.8Hz，闪变包络的初相角为0。闪变信号波形图如图3所示：The flicker signal is added in the whole time period of the normal voltage, the modulation degree of the flicker voltage envelope is 0.125, the frequency of the flicker envelope is 8.8Hz, and the initial phase angle of the flicker envelope is 0. The flicker signal waveform is shown in Figure 3:
应用Teager能量算子对重构信号进行检测，可得闪变包络随时间变化的波形图和检测误差结果，如图8所示：Using the Teager energy operator to detect the reconstructed signal, the waveform diagram and detection error results of the flicker envelope changing with time can be obtained, as shown in Figure 8:
从上图可明显得到，闪变包络检测误差极小，效果良好，随时间的变化与预先设定值一致。Teager能量算子能够准确的实现重构信号的检测。It can be clearly seen from the above figure that the flicker envelope detection error is extremely small, the effect is good, and the change over time is consistent with the preset value. The Teager energy operator can accurately detect the reconstructed signal.
综上所述，压缩感知理论适用于风力发电机组电能质量信号检测领域。In summary, the compressive sensing theory is applicable to the field of wind turbine power quality signal detection.
本发明实施例中通过将压缩感知理论，应用到风力发电机组电能质量采样检测领域，突破了传统的奈奎斯特采样定理，将采样和压缩同时进行，可大大减少采样数据量，缩短采样时间，降低对风力发电机组电能质量信号采样检测硬件系统的要求，便于数据存储和传输；且采用的稀疏随机测量矩阵对风力发电机组电能质量信号观测压缩处理效果比采用高斯随机矩阵和贝努力矩阵的计算复杂度低，且易于实现，也能降低对风力发电机组电能质量信号采样检测硬件系统的要求。In the embodiment of the present invention, by applying the theory of compressed sensing to the field of sampling and detection of power quality of wind power generating units, it breaks through the traditional Nyquist sampling theorem, and performs sampling and compression at the same time, which can greatly reduce the amount of sampling data and shorten the sampling time , reducing the requirements for the sampling and detection hardware system of the power quality signal of the wind turbine, which is convenient for data storage and transmission; and the sparse random measurement matrix adopted is better than that of Gaussian random matrix and Bernoulli matrix for the observation and compression processing of the power quality signal of the wind turbine The calculation complexity is low, and it is easy to implement, and can also reduce the requirements for the sampling and detection hardware system of the power quality signal of the wind power generating set.
以上公开的仅为本发明的几个具体实施例，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。The above disclosures are only a few specific embodiments of the present invention, and those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention, provided that these modifications and modifications of the present invention belong to the rights of the present invention The present invention also intends to include these modifications and variations within the scope of the requirements and their technical equivalents.
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