摘要
随着电网中采用高频电力电子器件制造的设备逐渐增多,配电网中的超高次谐波现象已经成为了一种亟需解决的新型电能质量问题。相较于传统谐波检测方法采样超高次谐波信号时产生的巨大数据量,压缩感知作为一种新型信号处理方法,在使用测量矩阵对稀疏信号进行亚采样后通过重构算法用较少的数据就能精确地恢复原始信号,有效降低了对采样端硬件的要求。提出了一种基于确定性测量矩阵与变阈值SAMP算法的压缩感知超高次谐波检测算法。首先该方法采用了一种由确定性随机序列构造的测量矩阵,这种确定性测量矩阵的结构与随机测量矩阵相比更易于传输与存储,同时具有和高斯随机矩阵相同的重构性能。其次,针对SAMP重构算法在频谱泄露时易发生稀疏度过估计的问题,提出了一种改进的变阈值SAMP算法,设置一个动态的阈值来控制算法中内积的选取,减少迭代中的误选。改进算法提高了超高次谐波检测的精度,降低了因频谱泄露和噪声造成的误差且更容易硬件实现。最后,通过仿真和实测结果证明了改进算法的准确性和有效性。
With the increasing use of high-frequency power electronic devices in power systems,the phenomenon of supraharmonics in distribution networks has become a new type of power quality problem that needs to be solved urgently.Compared with the huge amount of data generated by the traditional harmonic detection method,when sampling supraharmonics signals,compressed sensing is a new type of signal processing method.After using the measurement matrix to sub-sample the sparse signal to be measured,the original signal can be accurately restored with fewer data through the reconstruction algorithm,which effectively reduces the requirements on the sampling hardware.This paper introduces a supraharmonics measurement method based on a deterministic measurement matrix and VT-SAMP.First,the method uses a measurement matrix constructed from a deterministic random sequence.The structure of this deterministic measurement matrix is easier to transmit and store than a random measurement matrix,and it has the same reconstruction performance as a Gaussian random matrix.Second,aiming at the problem of the sparseness overestimation caused by spectrum leakage in the SAMP algorithm,this paper proposes an improved SAMP algorithm with Variable Threshold(VT-SAMP).It sets a dynamic threshold to control the selection of the inner product in the algorithm and reduce mis-selection in iterations.The improved algorithm enhances the accuracy of supraharmonics measurement and reduces the errors caused by spectrum leakage and noise.Finally,the accuracy and effectiveness of the improved algorithm are proved by simulation and actual measurement results.
作者
刘建锋
宋子恒
周勇良
孔培
LIU Jianfeng;SONG Ziheng;ZHOU Yongliang;KONG Pei(College of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2020年第21期75-83,共9页
Power System Protection and Control
基金
国家自然科学基金青年科学基金项目资助(51807114)。
关键词
超高次谐波
压缩感知
确定性测量矩阵
变阈值SAMP算法
supraharmonics
compressed sensing
deterministic measurement matrix
SAMP algorithm with variable threshold
