The Development of a $d$–$q$ Axis WPT-Based Digital Protection for Power Transformers

Abstract

This paper presents the analysis and development of a new digital differential protection for three phase (3 ) power transformers. The proposed digital protection is based on extracting high frequency sub-band contents present in the axis components of the differential currents in order to identify internal faults. The desired high frequency sub-band contents are extracted using a single-stage wavelet packet transform (WPT), which offers parameterizing the energy in the high frequency sub-band contents using a finite number of coefficients. The WPT coefficients contain information that offer accurate, fast, and reliable detection and classification of transient disturbances, including magnetizing inrush and internal fault currents that may be experienced by 3 power transformers. The WPT-based digital differential protection is implemented for off-line performance evaluation using differential currents collected from a 5 kVA, 3 , laboratory power transformer. Off-line test results demonstrate accurate, fast, and reliable detection, classification, and response to different types of fault and non-fault currents. These encouraging performances of the WPT-based digital differential protection are obtained with simple implementation, reduced computational burdens, and small memory requirements.Index Terms-Digital differential protection, digital filters, internal fault currents, magnetizing inrush current, synchronous rotating reference frame ( axis), three phase power transformers, wavelet analysis. NOMENCLATURE-point circular convolution operation. Continuous frequency.Discrete frequency. Scaling function.Wavelet function associated with . Set of real numbers. Inception angle. Set of integer numbers. Approximation signal at scale and shift .

Performance Evaluation of an Embedded $d$– $q$ WPT-Based Digital Protection for IPMSM Drives

“…When WPT analysis is applied to discrete signals, the 2 j frequency subbands are realized by a tree of half-band digital low-and high-pass filtering operations. The WPT can be mathematically stated for a discrete signal x[k] as [35], [36] x…”

“…This capability of WPT offers accurate processing of signals associated with transient disturbances in motor drives, including IPMSM drives [35], [36]. Fig.…”

“…The artificial neural network (ANN)-based digital protection has been developed and tested for motor drives (both induction motor and IPMSM drives). The structure of the ANN required, along with need for collecting data to train and design the ANN, has created major difficulties for utilizing the ANN-based digital protection in motor drives, including IMPSM drives [16], [18], [35], [36]. As of late, the MCSA approach has been realized by the time-frequency (TF) analysis, which is established by the integral transform, Hilbert transform, Cohen-class quadratic distributions, and recently, wavelet transforms.…”

“…Such interests are due to the ability of wavelet transforms, particularly the WPT, to offer accurate parametrization (with high frequency-time resolution) of signals with complex TF structures. Such signals can arise from various types of transient disturbances experienced by motor drives, including the IPMSM drive [24]- [36].…”

“…The need for training and specifying the layout of these processing steps has mandated significant computations, which have raised concerns for their online implementations. Despite the significant performance of the WPT-based digital protection, its integration with motor drives, including IPMSM drives, remains a major challenge [22]- [36]. This paper presents the implementation and performance evaluation of a new WPT-based digital protection for IPMSM drives.…”