Wavelet-Based Fast Discrimination of Transformer Magnetizing Inrush Current

摘要

Customers who need electricity of higher quality have recently been installing cogeneration facilities. They can avoid voltage sags and other distribution system-related disturbances by supplying electricity to important loads from their generation equipment. As another example, the FRIENDS highly reliable distribution system using semiconductor switches or storage devices based on power electronics technology, has been proposed. These examples illustrate that the need for high reliability of power supply in distribution systems is increasing. Fast relaying algorithms are indispensable in order to realize these systems. The author proposes a new method of discriminating a magnetizing inrush current and a short-circuit fault current by using the discrete wavelet transform (DWT). The DWT provides the function of detecting discontinuity of the current waveform. An inrush current occurs when a transformer core becomes saturated. The proposed method detects spikes of the DWT components derived from the discontinuity of the current waveform at both the beginning and end of the inrush current. Wavelet thresholding, a form of wavelet-based statistical modeling, was used to detect the spikes of DWT components. The proposed method was verified by experimental data obtained from field tests using a single-phase transformer and the proposed method was demonstrated to be effective.