关键词: 主瓣干扰, 谐波, 间谐波, 原子分解, 麻雀搜索算法

Abstract: In modern power systems,the issue of harmonic and interharmonic pollution is increasingly severe.Aiming at the bottleneck problem of balancing detection accuracy and computational efficiency in existing harmonic and interharmonic analysis methods,this paper innovatively proposes a joint optimization method that integrates the improved Sparrow Search Algorithm(SSA) with Orthogonal Matching Pursuit(OMP).By constructing an overcomplete sine atomic library based on continuous parameters,it breaks through the limitations of traditional discretized atomic search.Combining SSA for global optimization of atomic parameters in continuous space significantly improves matching accuracy.Meanwhile,by introducing an orthogonal iterative mechanism and an adaptive termination condition based on signal correlation,it effectively reduces redundant calculations and suppresses noise interference.Simulation results show that the proposed SSA-OMP algorithm achieves a maximum reconstruction signal-to-noise ratio of 49 dB in harmonic/interharmonic frequency,amplitude,and phase detection,with a frequency error below 0.013 4%,and its noise immunity is superior to traditional methods.Compared with the Particle Swarm Optimization-OMP algorithm,the computational efficiency is improved by 20%,providing an innovative solution with high accuracy and low complexity for real-time monitoring in complex harmonic scenarios of power systems.

Key words: Mainlobe interference, Harmonics, Interharmonics, Atomic decomposition, Sparrow search algorithm