Considering New Energy Access

With the large-scale access to non-linear equipment and new energy generation devices, power system harmonics tend to become more and more prominent, and the harmonic components of the system become increasingly complex. Compressive sensing techniques complete the compression of data in the sampling, which effectively reduces the amount of sampled signal data compared to traditional Nyquist sampling methods, overcoming the drawbacks of high complexity of compression at the sampling side and high hardware requirements. Therefore, in this paper, the sparsity characteristics of fundamental, harmonic and interharmonic power system signals are demonstrated theoretically and proposed a fundamental filtering self-adaptive matched pursuit algorithm (FF-SAMP) based on the characteristics. The algorithm in this paper has high accuracy in the estimation of harmonic phase quantities and maintains a certain superiority among the compared algorithms.