2017
DOI: 10.1016/j.egypro.2017.05.242
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Inrush Blocking Scheme in Transformer Differential Protection

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Cited by 15 publications
(3 citation statements)
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“…Figure 18 shows the results of detailed analyses of nonsinusoidal primary delta winding currents in no-load steady state. Qualitative analyses can also be freely extended to the selected fragments of the dynamic current and voltage waveforms where, e.g., the dominant harmonic component might be verified [12,39,40]. The exemplary results of analyses performed for the first period of the transient delta winding current of the center column are presented in Figure 19 and shown in Table 2; the participation of the second harmonic [6,26] may be observed here.…”
Section: Steady-state Assessmentmentioning
confidence: 97%
“…Figure 18 shows the results of detailed analyses of nonsinusoidal primary delta winding currents in no-load steady state. Qualitative analyses can also be freely extended to the selected fragments of the dynamic current and voltage waveforms where, e.g., the dominant harmonic component might be verified [12,39,40]. The exemplary results of analyses performed for the first period of the transient delta winding current of the center column are presented in Figure 19 and shown in Table 2; the participation of the second harmonic [6,26] may be observed here.…”
Section: Steady-state Assessmentmentioning
confidence: 97%
“…Inrush magnetizing currents (startup currents) in transformers are an important influence that increases the risk of incorrect operation of DFRs. The distinction of these currents from actual fault currents can be achieved by comparing the two current behaviors in terms of phase angles [73], [74]. In addition, analysis of the primary and secondary currents, the transformer end voltage and the voltage values at the load ends is also necessary to make the distinction between internal and external faults more accurate.…”
Section: Zubic Et Al Presented a New Dr Algorithm Based On Maximum Overlap Discrete Wavelet Transform (Modwt)mentioning
confidence: 99%
“…(1) Signal analysis using time-frequency analysis such as wavelet transform, s-transform, and Huang-Hilbert transform [4][5][6][7][8][9][10] (2) Classification algorithms and learning machines such as artificial neural networks and tree-based algorithms…”
Section: Introductionmentioning
confidence: 99%