A Novel Interpolated DFT Synchrophasor Estimation Algorithm With an Optimized Combined Cosine Self-Convolution Window
Tao Jin, Weifeng Zhang
Abstract
With the current power system being electronicized nowadays, synchrophasor estimation (SE) plays an increasingly critical role in the monitoring, analysis, and protection of the state of the power grid. One proposal has been brought to enhance the commonly used discrete Fourier transform (DFT) algorithm that has a large error due to the inherent spectral leakage and fence effect in asynchronous sampling by interpolations. This article proposes an SE algorithm based on an optimized combined cosine self-convolution (OCCSC) window. Using the sidelobe characteristics of the window functions as the evaluation index, an optimized combined cosine window is obtained by the accelerated particle swarm optimization (APSO) algorithm. The window function's self-convolution is used to further expand its excellent characteristics. Based on these characteristics, combined with interpolated DFT, simulations and experimental verifications compared with other algorithms show the effectiveness of the proposed algorithm.