Divergence Distance Based Index for Discriminating Inrush and Internal Fault Currents in Power Transformers

نویسندگان

چکیده

This article puts forward a new algorithm based on Kullback–Leibler divergence (KLD) for discriminating inrush and internal fault currents in power transformers. Specifically, the main idea of this is to utilize current signal discrepancy distribution with ideal waveforms. To such an aim, proposed index reproduces differential signal. Utilizing fast modified least squares technique, generated. Applying reconstructed sinusoidal waveforms KLD indicator, from waveform discriminates currents. Also, internal/external identification introduced that utilizes phase content signals transformers (CTs) both sides distinguish external faults, especially faults accompanied CT saturation. As result, method can currents, with/without saturation, during transformer energization. The performance evaluated using practically recorded data further compared state art.

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ژورنال

عنوان ژورنال: IEEE Transactions on Industrial Electronics

سال: 2022

ISSN: ['1557-9948', '0278-0046']

DOI: https://doi.org/10.1109/tie.2021.3082071