中国电机工程学报2024，Vol.44Issue(24)：9559-9570,中插5,13.DOI:10.13334/j.0258-8013.pcsee.231404
基于稀疏字典原子共享的电力系统谐波动态监测方法
A Dynamic Harmonic Monitoring Method for Power System Based on Sparse Dictionary Atom Sharing
摘要
Abstract
With the wide access of novel load and distributed generations(DGs),the harmonic problem in power system is becoming more and more prominent.Harmonic monitoring at grid connection points is the premise of responsibility division,source tracing and suppression of harmonic pollution.Aiming at the problem that harmonic signal is difficult to monitor due to its strong randomness and subtle characteristics,this paper proposes a dynamic harmonic monitoring method in power system based on sparse dictionary atoms sharing.First,the characteristics of harmonic in power system are analyzed,and a harmonic dynamic monitoring architecture based on sharing and multiplexing the over completed dictionary atoms of compressed sensing is proposed to realize continuous dynamic sampling of power grid operation data.Then,a residual energy-based sparsity adaptive matching pursuit(REB-SAMP)algorithm is proposed,which characterizes the degree of sparse decomposition of the original data by calculating the residual energy after each iteration.Based on this residual energy,an iterative termination criterion and a variable step-size strategy are formulated for the algorithm.In addition,by cascading Gabor over-complete sparse dictionary and Fourier sparse dictionary,the super-complete synthetic dictionary is constructed,which improves the sparse representation performance for harmonic monitoring data.Finally,a distributive generation system is built based on PSCAD/EMTDC simulation platform to verify the rationality and effectiveness of the proposed algorithm.The simulation shows that the proposed algorithm is easier to detect the harmonics at the points of common coupling(PCC),and has the advantages of higher reconstruction accuracy,better convergence and stronger anti-noise performance.关键词
压缩感知/完备稀疏字典/稀疏分解/谐波监测/重构算法Key words
compressed sensing/completed sparse dictionary/sparse decomposition/harmonic monitoring/reconstruction algorithm分类
信息技术与安全科学引用本文复制引用
李石强,王鹤,于华楠..基于稀疏字典原子共享的电力系统谐波动态监测方法[J].中国电机工程学报,2024,44(24):9559-9570,中插5,13.基金项目
国家自然科学基金项目(面上基金)(52177074).Project Supported by National Natural Science Foundation of China(General Program)(52177074). （面上基金）
