摘要
电力系统中电力电子产生的谐波数量不断增加,谐波问题是一个重要的问题。本文提出了一种改进的互质采样(Coprime sampling,CS)方案,用于谐波和间谐波频率估计。所提方案使用稀疏采样来降低采样率,并将其与现代频谱估计算法相结合。特别是,使用分段互质采样(Segmented coprime sampling,SCS)方法,然后使用求根多重信号分类(Root-multiple signal classification,root-MUSIC)算法代替常用的MUSIC算法可以减少计算工作量并获得准确的频率估计。仿真结果表明,该方法在估计精度上优于传统的均匀采样(Uniform sampling,US)方法。
The number of harmonics generated by power electronics in power systems is increasing,and the harmonic problem is a significant concern.In this paper,we propose an improved coprime sampling(CS)scheme for harmonic and interharmonic frequency estimation.The proposed scheme uses sparse sampling to reduce the sampling rate significantly and combines it with modern spectral estimation algorithms.Then,the segmented coprime sampling(SCS)method replaces the traditional CS,effectively reducing the sampling rate and the hardware system’s workload.In addition,the root-multiple signal classification(root-MUSIC)algorithm returns the commonly used MUSIC algorithm,which guarantees estimation accuracy and significantly reduces computational complexity.The simulation results show that the proposed scheme outperforms the traditional uniform sampling(US)method in estimation accuracy.
作者
岳衡
张小飞
YUE Heng;ZHANG Xiaofei(Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,P.R.China;College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,P.R.China)
基金
supported by the National Natural Science Foundation of China(Nos.61631020,61971217,61971218)
the Natural Science Foundation of Jiangsu Province(No.BK20200444)
the National Key Research and Development Project(No.2020YFB1807602)。
关键词
互质采样
间谐波
ROOT-MUSIC算法
频率估计
coprime sampling
interharmonic
root-multiple signal classification(MUSIC)algorithm
frequency estimation
