File Exchange

image thumbnail

Three-phase SFT-PLL synchronization block

version 1.0.0 (131 KB) by Usama Mohamed
Frequency Adaptive Sliding Fourier Transform for Synchronizing VSCI to the Utility Grid


Updated 21 Nov 2019

View License

Sliding Discrete Fourier Transform (SDFT) is very efficient regarding computational load and possesses a very fast phase angle detection with excellent harmonic rejection at nominal frequency. However, at the off-nominal frequency, SDFT generates errors in both magnitude and phase angle due to spectral leakage. Also, its harmonic rejection is greatly impaired under such conditions. The attached block introduces a workaround for Fourier Transform (in sliding continuous SFT and sliding discrete SDFT flavors) to handle this disability under off-nominal frequency while avoiding variable-rate sampling. The method used to implement SFT is also combining the symmetrical component analysis technique to ensure that we get only the phase angle, magnitude and frequency of the positive sequence attributes. Sliding Fourier Transform (SFT) is used as a phase detector for a phase-locked loop whose output frequency is used to drive the SFT. The model included compares the performance of the proposed SFT-PLL with that of the Decoupled Stationary Reference Frame PLL (dαβPLL) which is one of the widely used techniques in industrial applications. Examining the results prove that SFT-PLL is superior to dαβPLL. Hence, it can be effectively used in synchronizing VSI to weak and micro-grids particularly under sever unbalance, harmonic distortion and DC offset.
The mathematics and the explanation of the block structure is given in :
"Frequency-adaptive sliding Fourier transform for synchronizing VSI to the grid"
International Journal of Power Electronics and Drive Systems 10(2):1034
DOI: 10.11591/ijpeds.v10.i2.pp1034-1048

Cite As

Usama Mohamed (2020). Three-phase SFT-PLL synchronization block (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (0)

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags