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New Algorithm to Identify Inrush Currrent Based on Improved EMD

Author: ChenDaZhuang
Tutor: HuangJiaDong
School: North China Electric Power University
Course: Proceedings of the
Keywords: Transformer primary protection Empirical Mode Decomposition Modal aliasing False modal
CLC: TM41
Type: Master's thesis
Year: 2011
Downloads: 47
Quote: 0
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Abstract


Power transformers in the power system is particularly important equipment , and the safe operation of the substation even the operation of the power system will play a crucial Has been differential protection is the main protection of the transformer . In this paper, based on Hilbert - Huang transform (HHT) core algorithms - empirical mode decomposition (EMD) to identify new transformer inrush current method to solve the transformer differential protection magnetizing inrush often malfunction . Empirical Mode Decomposition (EMD) is the core algorithm of the Hilbert - Huang transform (HHT) is a partial , based entirely on data adaptive signal decomposition method , very suitable for the analysis of non-stationary multi- component signals . Exist for classic EMD modal confusion , prone to false lack of frequency components , this paper presents a wavelet analysis method to preprocess the signal , the signal is broken down into a series of narrow-band signal , and then apply the EMD method makes each order IMF are single constituent signal , while using the normalized correlation processing to remove false frequency components . Using the inrush current non- stationary signals , frequency domain led IMF proposed an extraction characteristics to identify the transformer inrush current . Theoretical analysis and dynamic simulation experimental results show that this method can correctly distinguish between magnetizing inrush and fault current , and fast judgments .

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CLC: > Industrial Technology > Electrotechnical > Transformers, converters and reactors > Power transformers
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