Current Transformer Saturation Detection Research Articles

Detection of Current Transformer Saturation Based on Machine Learning

One of the tasks in the operation of electric power systems is the correct functioning of the protection system and emergency automation algorithms. Instrument voltage and current transformers, operating in accordance with the laws of electromagnetism, are most often used for information support of the protection system and emergency automation algorithms. Magnetic core saturation of the specified current transformers can occur during faults. As a result, the correct functioning of the protection system and emergency automation algorithms is compromised. The consequences of current transformers saturation are mostly reflected in the main protections of network elements operating on a differential principle. This work aims to consider the analysis of current transformer saturation detection methods. The problem of identifying current transformer saturation is reduced to binary classification, and methods for solving the problem based on artificial neural networks, support vector machine, and decision tree algorithms are proposed. Computational experiments were performed, and their results were analyzed with imbalanced (dominance of the number of current transformer saturation modes over the number of modes with its normal operation) and balanced classes 0 (no current transformer saturation) and 1 (current transformer saturation).

Current Transformer Saturation Detection Method Based on Artificial Neural Network

When current transformer is saturated, mainly due to the presence of an exponentially decaying DC component in the fault current, its secondary current has a distinctive distorted waveform which significantly differs from its primary (true) waveform. It leads to an underestimation of the secondary current value calculated by the relay protection compared to its true value. Thus, in its turn, results in trip time delay or even in a relay protection devices operation failure, since its settings and algorithms are calculated and designed on the assumption that the secondary current waveform is sinusoidal and proportional to the primary. And since, when using classical electromagnetic current transformer, it is impossible to exclude the possibility of its saturation, the detection of such abnormal condition is an urgent technical problem. The article proposes to use an artificial neural network for this purpose, which, together with the traditional method of saturation detection based on adjacent secondary current samples comparison, allows implementing a fast and reliable current transformer saturation detector. The article details the stages of the practical implementation of such an artificial neural network. The MATLAB-Simulink environment was used for assess the proposed saturation detector operation. The experiments that had been performed confirmed that proposed method provides fast and accurate saturation detection within the wide range of the power system and current transformer parameters change.

Fast Detection of Current Transformer Saturation Using Stacked Denoising Autoencoders

Malfunctions in relay protection devices are predominantly caused by current transformer (CT) saturation which produces distortion in current measurements and disturbances in power system protection. The development of deep learning in power system protection is on the rise recently because of its robustness. This study presents a CT saturation detection where the secondary current becomes distorted. The proposed scheme offers a wide range of saturation detection and consists of a moving-window technique and stacked denoising autoencoders. Moreover, Bayesian optimization was used to minimize the difficulty of determining neural network structure for the proposed approach. The performance of the algorithm was evaluated for a-g faults on 154 kV and 345 kV overhead transmission line in South Korea. The waveform variation has been generated by PSCAD for different scenarios that heavily influence CT saturation. Moreover, a comparative analysis with other methods demonstrated the superiority of the proposed DNN method. With the proposed algorithm to detect CT saturation, it significantly yielded high accuracy and precision for CT saturation detection which were approximately 99.71% and 99.32%, respectively.

CT Saturation Detection and Compensation: A Hybrid Physical Model- and Data-Driven Method

Current transformer (CT) saturation is one of the dominant causes of relay protection devices’ malfunctions, which pose a threat to the safe operation of the power system. To address this problem, we propose a hybrid physical model- and data-driven method. The method firstly detects the CT saturation and then compensates it to reproduce the real waveform. Considering the multi-factor and strong nonlinearity of CT saturation, a data-driven model, namely the Fully Convolutional Network (FCN), is built to detect the operation status of CT. As for the compensation, a physical model of short-circuit current is used for its conciseness and universality. Through tactfully integrating the data model and the physical model, the proposed method is endowed with two major merits: the arduous adjustment of universal thresholds and parameters in existing methods is avoided, and the deficiency in generalization and interpretability of the data-driven method is assuaged. Simulation and experimental results verify the effectiveness of the proposed method. Furthermore, its application potential to future protection is explored.

Hardware implementation and real time performance evaluation of current transformer saturation detection and compensation algorithms

This paper presents a hardware implementation of two current transformer (CT) saturation detection methods and one distorted signal reconstruction method. Those methods have been implemented previously only in software. To evaluate the algorithms performance, a real time hardware in the loop system was implemented with several test scenarios forcing CT saturation.The paper highlights the influence of the quantization error generated by the analog-to-digital-converter in the reconstruction of distorted signal process and introduces a method to determine the best parameters to reconstruct the distorted current signal.The methods used have shown precision and high speed in detecting and compensating distorted current signal in real time, even for the worst CT saturation cases.

A New Differential Protection Scheme for Busbar Using d–q–0 Transformation

This paper presents a new differential protection scheme for busbar using d–q–0 transformation. The proposed method is based on derivation of operating and restraining currents by utilizing direct axis (d) component of current transformer (CT) secondary current signals of all bays. The dual slope relay characteristic (derived from the operating and restraining current) of the proposed scheme operates in conjunction with a CT saturation detection algorithm and hence, provides better stability during external faults with CT saturation. The performance of the proposed scheme has been evaluated by modeling a 400 kV sub-station with two different busbar configurations, namely Breaker-and-Half configuration (BHC) and single breaker double-bus configuration (SBDBC) in PSCAD/EMTDC software package. The proposed algorithm has been tested for various fault cases with diversified system and fault parameters. The proposed scheme is highly sensitive against in-zone faults even with a considerable value of fault resistance as the average fault detection time remains within one-and-half cycle. At the end, a comparative evaluation of the proposed scheme with the conventional bus differential protection scheme (87B) clearly indicates its superiority in terms of stability against close-in out-of-zone faults with CT saturation and sensitivity for high impedance internal faults.

Framework for current transformer saturation detection and waveform reconstruction

Due to current transformer (CT) saturation, the secondary current waveform may contain distortions which results in mal-operation of the protective system. This study presents a framework that attempts to detect and reconstruct saturated secondary current of the CT. To such aim, first an algorithm is proposed which detects and discriminates between normal and abnormal condition. This algorithm which is based on high-order derivatives and statistical criterion, classifies load change, inrush current and fault condition. In addition, this algorithm is designed so that it detects the first time that CT becomes saturated. After fault detection and phase fault selection, based on analytical and comprehensive formulations, the parameter of fault current signal is calculated in the sub-cycle. Moreover, the dynamic behaviour of the CT is considered in the waveform reconstruction. Several case studies are carried out to investigate the performance of the proposed method. Simulation results show that proposed method can effectively classify the inrush current and fault signal even in the CT saturation condition. Also, under different CT saturation condition, proposed method quickly and precisely detects and reconstructs saturated waveform without sacrificing details.

A Wavelet-Based Transformer Differential Protection With Differential Current Transformer Saturation and Cross-Country Fault Detection

The current transformer (CT) saturation phenomenon has been one of the main problems for the power transformer differential protection, leading to incorrect current measurements and relay misoperation. This paper proposes a fast and efficient transformer differential protection scheme with additional differential CT saturation and cross-country fault detection modules after the external fault detection, all of them based on the differential wavelet coefficient energy with border distortions in order to stabilize the relay during external faults and distinguish accurately CT saturation from cross-country internal faults. The proposed method was assessed by using representative simulations of internal faults, transformer energizations, and external faults with CT saturation followed by cross-country internal faults, and good results were achieved.

A Comparative Study of Morphological Gradient and Its Improved Form for CT Saturation Detection

Magnetization of a Current Transformer (CT) is a non-linear characteristic, which can cause distortion in its secondary waveform, causing malfunction of protective relay. In this paper, two algorithms based on mathematical morphology, morphological gradient and improved morphological gradient have been compared for detection of CT saturation. The improved morphological gradient is effective in removing noise and separating transient information from the signal. Starting and end time of saturation can be detected using this algorithm.

Design and testing of a bus differential protection scheme using partial operating current (POC) algorithm

This paper presents a novel bus differential protection scheme that provides enhanced immunity against mis-operation resulted from current transformer (CT) saturation during close-in external faults and better sensitivity for internal faults. The proposed scheme incorporates a fault discrimination algorithm based on partial operating current (POC) characteristic making the scheme capable of discriminating high current internal and external faults even with CT saturation. A supervision technique based on CT saturation detection is also included in the scheme design to increase the sensitivity of the proposed relaying scheme for very high impedance internal faults. A relay model is built in Matlab platform based on the proposed scheme and the performance is validated using a transmission network simulated in Electromagnetic Transients Program (EMTP) for various fault scenarios. Documented results show the proposed scheme improves the performance in terms of reliability, sensitivity, and selectivity over traditional bus differential schemes.

Current Transformer Saturation Detection Using Morphological Gradient and Morphological Decomposition and Its Hardware Implementation

In this paper, the improved morphological gradient algorithm and the morphological decomposition algorithm are used to detect the saturated sections of a secondary current, and the detection results are combined by the AND logic so as to provide a more accurate and reliable detection result. The proposed method is implemented in a system on chip, whose core is a field-programmable gate array. To evaluate the performance of the proposed method as well as its hardware implementation, a simple double-side power supply system model is built in RSCAD, and a test platform involving a real-time digital simulator is set up accordingly. The simulation results have shown that the proposed method can correctly identify the saturated sections under various conditions, and its hardware implementation has illustrated that the proposed method can be used in real time in practice.

Adaptive busbar differential relaying scheme during saturation period of current transformers based on alienation concept

This study presents an advanced technique provided with adaptive differential relay characteristics for avoiding current transformer (CT) saturation effects. The proposed technique uses the alienation and differential protection principles to make adaptive logic; if no CT saturation is detected, the differential principle alone is capable of tripping the busbar. If CT saturation is detected, both the alienation and differential principles must pickup in order to trip. The alienation coefficient is useful in CT saturation detection, evaluation of CT saturation degree and adapting the differential relay characteristics during saturation period of CTs to avoid false operation in the event of external faults. The differential current and alienation coefficient are calculated from two terminal currents of the busbar. The proposed protective scheme has several attractive features, including the simplicity of on-line implementation, not affected by the remanent flux in the CT core, and it is independent of the CT parameters/characteristics and secondary burden. A real 19.57 kV busbar is simulated using Alternate Transients Program/Electro-Magnetic Transient Program and MATLAB packages to examine the suggested scheme under different types of faults. Under normal operating conditions and external faults, the scheme remains stable and it operates only for the case of internal faults. Moreover, it is unaffected by CT saturation.

A precise scheme for detection of current transformer saturation based on time frequency analysis

Abstract Current Transformers (CTs) are prone to saturation due to large amplitude of fault current and existence of decaying Direct Current (DC) offset. Since the CT saturation leads to mal-operation of protective relays, detection and correction of saturated currents is one of the most important challenges in the power systems protection. In this paper, a new algorithm is presented for detection of CT saturation time interval by using the Improved S-Transform (IST). Simultaneously, IST can yield a complete visualization of signal in both time and frequency domains. An index based on instantaneous power of the CT secondary current is calculated using the IST output matrix. Then, the saturation region is estimated by determining the maximum and minimum values of the proposed index in the time domain. Comprehensive simulations are implemented using PSCAD/EMTDC software. Main parameters which have direct effect on the saturation levels are considered in simulation studies. As extremum points of the proposed index are determined for detection of saturation regions, the proposed method is not affected by CT parameters. The obtained results show that the proposed algorithm can precisely detect CT saturation time intervals even in noisy conditions.

Detection of current transformer saturation based on variational mode decomposition analysis

Sometimes, current transformers (CTs) are saturated in power systems due to increase of flux passing through the CT core. The distorted CT secondary current can lead to maloperation of protective relays. In this study, a new algorithm is proposed for detection of saturation interval by analysing secondary current signal using variational mode decomposition (VMD). The VMD can decompose signals into different modes which are concentrated around centre frequencies. The start and end points of saturation regions are estimated by using decomposed modes signals. Comprehensive simulations are implemented in PSCAD/EMTDC environment while the main parameters which have direct effect on saturation levels are considered in simulation studies. The performance of the proposed method is evaluated in different conditions: light, moderate, severe and AC CT saturation conditions. The promising obtained results of real data test show that the proposed method can detect the CT saturation time intervals with high accuracy in practical applications.

Current-Transformer Saturation Detection Using Savitzky-Golay Filter

A new application of the Savitzky-Golay (SG) filters in current-transformer saturation detection is proposed. The ability of the SG filters to handle noisy signals improves the robustness of the detection process in the presence of noise while requiring only low computational effort.

Waveshape recognition technique to detect current transformer saturation

This study presents a technique to identify current transformer (CT) saturation based on waveshape properties of the CT secondary current. First, a variable-length window, designated as the symmetry assessment window (SAW), is defined. Certain distinctive features of the distorted and undistorted currents inside the SAW are extracted by defining two variance functions. Using the extracted features, a new criterion is introduced to detect CT saturation. The proposed method is unaffected by fault current characteristics and CT variable parameters, such as CT burden, core remanence and its magnetising curve. One major contribution of this method is allowing cheaper measurement systems for busbar protection by easing the relay CT requirements. Analysis of real power system fault currents in a real-time manner using a hardware setup is accompanied by PSCAD/EMTDC simulation results to verify the accuracy and high speed of the proposed technique in various conditions.

A New Method of Current-Transformer Saturation Detection in the Presence of Noise

The nonlinear characteristics of magnetization of a current transformer (CT) can cause waveform distortion in the secondary current, which may result in malfunction of protective relays. This phenomenon is known as CT saturation. The accurate saturation detection, with the use of digital-signal-processing techniques applied to secondary current, plays an important function in solving the problems caused by the saturation. This paper presents a new method of saturation detection, based on the first difference of the low-noise Lanczos filter. The formulation of the adaptive threshold according to the level of the signal-to-noise ratio (SNR) is presented and the detection algorithm is implemented, tested, and compared with the 3rd difference function method. The tests were performed using distorted secondary current signals generated by the real-time digital simulator and corrupted by several levels of white Gaussian noise. The results showed a high detection capability of the proposed algorithm regardless of the CT characteristics, the secondary burden, and the fault characteristics. In addition, the method showed to be robust against noise up to 40-dB SNR and suitable for real-time implementation.

New Algorithm for current transformer saturation detection and compensation based on derivatives of secondary currents and Newton's backward difference formulae

This study presents a new current transformer (CT) saturation detection and compensation algorithm. The proposed algorithm depends on a saturation detection index ( D n ) which is derived by using the derivatives of the current signals and Newton's backward difference formulae. The calculated index is continuously compared with an adaptive threshold ( T h ) to estimate the start and the end point of CT saturation. A low-pass first-order Butterworth filter is used to suppress noise and harmonics which may be present in CT secondary current. The proposed saturation detection algorithm has been tested by considering different values of remanent flux, fault type, fault inception angle, burden resistance, decaying DC component of fault current and noise. At the same time, modified discrete Fourier transforms-based compensating algorithm has also been proposed to reconstruct the saturated samples. Validation of the proposed scheme is also performed on a developed laboratory prototype. A comparative evaluation of the proposed algorithm is also performed with the existing schemes. A series of test results from the simulation software and the laboratory prototype show the effectiveness of the proposed scheme.

CT Saturation Detection Based on Waveshape Properties of Current Difference Functions

Derivative-based approaches have been widely used for current-transformer (CT) saturation detection. Previous approaches dealt with the magnitude of current derivatives. This paper, however, proposes a novel CT saturation detection algorithm that is subject to the waveshape properties of current derivatives. Two indices are introduced to extract certain key features of a current waveshape using its first two difference functions. Combining these two indices, CT saturation is rapidly and reliably detected. This method operates correctly irrespective of CT parameters, fault current characteristics, and power system conditions. Derivative-based techniques are suspected to be noise sensitive. Meanwhile, appropriate measures are taken, and the robustness of this method against noise is guaranteed. Extensive analysis of various real and simulated currents confirms that this algorithm can meet the rigorous speed and accuracy standards of industrial relays.

Current Transformer Saturation Detection Using Gaussian Mixture Models

This paper presents a novel current transformer (CT) saturation detection approach based on Gaussian MixtureModels (GMMs). High accuracy is the advantage of this method. GMMs are trained with secondary current of CT. Theappropriate performance of the proposed method is tested by simulation of different fault conditions inPSCAD/EMTDC software. The results show that the trained GMMs can successfully detect CT saturation with highaccuracy.