Supraharmonics measurement algorithm based on CS-SAMP

In recent years, with more and more electrical equipment employed in the power system, the content of supraharmonics in distribution networks has gradually increased, which has become one of the new power quality problems in power grid. This paper proposed a supraharmonics measurement method based on compressed sensing (CS) with sparsity adaptive matching pursuit (SAMP),to solve existing supraharmonics measurement algorithm cannot accurately predict the sparseness of harmonic signals. The method is based on fast Fourier transform (FFT) coefficients and Dirichlet kernel function, combined with an interpolation factor, constructs a high-precision compressed sensing model. At the same time, this paper introduces the concept of sparsity adaptive, and proposes the frequency and amplitude of supraharmonics in the signal can be detected by the SAMP algorithm. The improved algorithm improves the accuracy of the supraharmonics reconstruction amplitude and reduces the error caused by the inability to estimate the sparseness of the signal to be detected. The simulation results demonstrate the accuracy and effectiveness of the improved algorithm.