A continuous wavelet and fast fourier transform-based single-phase adaptive auto-reclosing scheme for ehv transmission lines

This paper presents a hybrid fault type identification technique based on continuous wavelet transform (CWT) and fast fourier transform (FFT) algorithm for an adaptive single-phase auto-reclosing scheme. Fast fault type identification i.e., identification between temporary and permanent fault is essential in protection algorithms. Integration of HVDC transmission links have made the protection system more complex. The HVDC converters cannot withstand high fault current for long time and disconnect for self-protection; consequently, the entire HVDC grid/link can be lost resulting a large blackout. Therefore, false detection of fault type on the AC side may challenge the reliability of the entire AC/DC power system. Hence, an adaptive auto-reclosing scheme based on CWT with the FFT algorithm (CWTFT) is presented in this paper. The proposed algorithm recognizes the fault type and arc extermination moment in least dead time. The temporary and permanent faults are identified based on the energies of CWTFT coefficients; the energies higher than the threshold level indicate that the fault is temporary. Subsequently, in case of a temporary fault, the arc extermination instant is estimated by the total harmonic distortion values; the values lower than the threshold level indicate that the arc is completely exterminated and it’s safe to initiate reclosing. The performance of the algorithm is verified on Cassie and Kizilcay arc models with both transmission line types i.e., (compensated and uncompensated) under a diversity of fault conditions. The proposed technique is tested on a model developed in MATLAB using practical parameters. The results indorse the effectiveness of the proposed scheme in single-phase auto-reclosing applications by achieving minimum dead time.