TY - JOUR T1 - Wavelet transform as a postprocessing diagnostic tool for fault identifications of high-voltage direct current transmission system AU - Sanjeevikumar, P. AU - Blaabjerg, Frede Y1 - 2016/04/12 PY - 2016 DA - 2017/01/01 N1 - doi: 10.1139/facets-2015-0005 DO - 10.1139/facets-2015-0005 T2 - FACETS JF - FACETS SP - 17 EP - 26 VL - 1 PB - Canadian Science Publishing N2 - This short communication focuses on exploiting the inherent advantages of discrete wavelet transformation (DWT) as a diagnostic tool for post-processing and for identifying the faults that occur in the standard high-voltage direct-current (HVDC) transmission network. In particular, a set of investigations are developed and examined for single-line-to-ground fault on the generation and on the load side converter, and DC-link fault. For this purpose, a standard 12-pulse line-commutated converter (LCC)-HVDC transmission network along with the DWT algorithm is numerically modeled in the MATLAB/PLECS simulation software. Furthermore, in this paper, a set of designed faulty conditions are predicted using the output of DWT and the results of numerical simulation are presented. Results are in good agreement with expectations to prove that DWT is an effective tool for fault diagnostics. AB - This short communication focuses on exploiting the inherent advantages of discrete wavelet transformation (DWT) as a diagnostic tool for post-processing and for identifying the faults that occur in the standard high-voltage direct-current (HVDC) transmission network. In particular, a set of investigations are developed and examined for single-line-to-ground fault on the generation and on the load side converter, and DC-link fault. For this purpose, a standard 12-pulse line-commutated converter (LCC)-HVDC transmission network along with the DWT algorithm is numerically modeled in the MATLAB/PLECS simulation software. Furthermore, in this paper, a set of designed faulty conditions are predicted using the output of DWT and the results of numerical simulation are presented. Results are in good agreement with expectations to prove that DWT is an effective tool for fault diagnostics. 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