Current Transformer Saturation Research Articles

PHASE ANGLE SHIFT AND SLOPE BASED RESTRAINT FOR INDIRECT SYMMETRICAL PHASE SHIFT TRANSFORMER PROTECTION

This study presents a method to limit the functioning of the differential relay during the different operating conditions of an Indirect Symmetrical Phase Shift Transformer (ISPST). The proposed method depends on two thresholds; phase angle shift (PAS) between two ends of an ISPST to discriminate internal faults and inrush conditions from normal, over-excitation, and external fault conditions and slope of differential current helps to discriminate the situation of internal fault from inrush. In the first step of the algorithm, the PAS-based threshold discriminates normal, over-excitation, and external fault conditions from magnetizing inrush and internal fault conditions. In the second step, the slope-based threshold discriminates magnetizing inrush from internal fault conditions. The reliability of the proposed method has also been examined under the condition of current transformer saturation due to heavy external faults. Additionally, the comparison of the suggested and conventional methods is discussed to check the superiority of the proposed method. The proposed method eliminates the need for phase angle shift correction in the suggested method. A variety of faults in the series and excitation unit are simulated using the PSCAD/EMTDC platform to verify the approach method.

A new unsynchronized fault location approach based on sequence voltage profiles and a multiconductor line detailed model: Application to symmetrical transmission lines

This paper presents a new, improved approach to fault location in long and very long transmission lines, which uses measurements at both terminals of the line that do not need to be synchronized, using the satellite time-reference. The new method employs symmetrical component sequence voltage profiles that are computed using an innovative approach in which the detailed three-phase model of a multiconductor transmission line is represented as the series connection of several chain matrices. This allows the new method achieve the best performance, when compared to other 4 similar fault location approaches, requiring measurements at both terminals of a symmetrical line, considering all types of faults, under realistic variations in variables and parameters of the test system, including the effect of saturation of current transformers, and arc faults. The main advantage of this proposed technique is that it can be applied with no major changes in symmetrical and unsymmetrical transmission lines keeping its good performance. In addition, division of the line in chain matrices allows the new proposed approach to be applied in non-homogeneous lines. In this paper, for space reasons, the new approach is initially applied to symmetrical (ideally transposed) transmission lines only, with very successful and encouraging results.

A new differential protection scheme based on Synchro-squeezing transform applied to AC Micro-Grid

In recent years, the protection of a microgrid has been a substantial challenge. This paper performs a differential protection scheme for the micro-grid based on Synchro-Squeezing Transform (SST). The proposed scheme protects the micro-grid in different modes i.e. islanded or grid-connected mode. Also, it is investigated in the ring and radial configuration. In the proposed scheme, currents on two sides of the line are measured by current transformers (CTs), and then differential current (IDiff) is calculated. This current is applied to extract the absolute value of the summation of the square root (ASSR). In this stage, transient and external faults without CT saturation and different switching such as connected or disconnected load/capacitor/distributed generation are detected from different internal faults. In the next stage, the frequency components of SST (FCSST) are extracted. By this feature, external fault and cross-country fault with CT saturation are detected. The proposed scheme is evaluated in noisy conditions, fault in different section of line with high resistance fault (HRF), and high impedance faults (HIF) of line. The micro-grid is simulated in PSCAD/EMTDC by various distributed generation (DG) like wind generation and photovoltaic systems penetrated at different buses. The proposed protection scheme is coded in MATLAB. The simulations represent the proposed protection scheme is correctly discriminate external and internal faults. At the same time, the method is immune to CT saturation and cross-country faults.

A Telegrapher’s equations-based implicit finite difference solution for fault location with current transformer saturation

This paper introduces a fault location method based on time analysis, utilizing synchronized data collected from both ends of the faulted line. The data is obtained either from Common Format for Transient Data Exchange (COMTRADE) files or Sampled Measured Value (SMV) of the IEC-61850 protocol. The method proposed in this study employs the implicit finite difference solution to the Telegrapher’s equations. In certain fault scenarios, such as when one or both transformers experience saturation, a narrow time window of data can be utilized to accurately pinpoint the fault location. The implicit solution method is unconditionally stable and therefore decouples the choice of the line discretization step from the sampling time interval, which is commonly required to maintain numerical stability of the explicit strategies for fault location. Furthermore, the numerical stability of the implicit process allows for devising a systematic search procedure that improves the accuracy of the calculated fault location, regardless of the transmission line length. By conducting numerical comparisons with an explicit time-domain fault locator and recent frequency-domain algorithms, the superiority of the proposed approach becomes evident. The results highlight the significant improvements achieved through the utilization of this method. Specifically, the results demonstrate that Telegrapher’s Equations implicit finite difference solution maintains accuracy under current transformer saturation, as it can locate the fault using data from a brief interval where the current transformer is not saturated.

A novel dual-core current transformer based on TMR sensor and its measuring characteristics

Current transformers (CTs) are the most widely used measurement instrumentation in power grids. Nevertheless, CT saturation gives rise to large measurement errors, which may have bad repercussions for the power system. In order to deal with the problem of CT saturation, a novel dual-core current transformer based on tunnel magnetoresistance sensor (DTCT) is proposed. Theoretical analyses, finite element method (FEM) simulations and accuracy tests are carried out to validate the practicability and effectiveness of the proposed DTCT. The simulation and experimental results manifest that the steady-state and transient characteristics of the DTCT are outstanding.

Deep Learning-Based Algorithm for Internal Fault Detection of Power Transformers during Inrush Current at Distribution Substations

The reliability and stability of differential protection in power transformers could be threatened by several types of inferences, including magnetizing inrush currents, current transformer saturation, and overexcitation from external faults. The robustness of deep learning applications employed for power system protection in recent years has offered solutions to deal with several disturbances. This paper presents a method for detecting internal faults in power transformers occurring simultaneously with inrush currents. It involves utilizing a data window (DW) and stacked denoising autoencoders. Unlike the conventional method, the proposed scheme requires no thresholds to discriminate internal faults and inrush currents. The performance of the algorithm was verified using fault data from a typical Korean 154 kV distribution substation. Inrush current variation and internal faults were simulated and generated in PSCAD/EMTDC, considering various parameters that affect an inrush current. The results indicate that the proposed scheme can detect the appearance of internal faults occurring simultaneously with an inrush current. Moreover, it shows promising results compared to the prevailing methods, ensuring the superiority of the proposed method. From sample N–3, the proposed DNN demonstrates accurate discrimination between internal faults and inrush currents, achieving accuracy, sensitivity, and precision values of 100%.

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).

A New Approach to Current Transformer Saturation Compensation for Transmission Line Differential Protection

A non-linear autoregressive network with external inputs (NARX) model to reconstruct the current transformer (CT) secondary waveform distortion in the presence of protected transmission lines is presented. The qualitative analysis carried out on the autonomous model reveals the accurate performance of the current differential relay, because of the ability of the NARX to make accurate predictions and signal reconstruction even when faced with noisy or incomplete datasets. The suggested method uses samples of the line-protected remote current signal to produce a desired waveform. The unsaturated section is artificially expanded because it can estimate up to one sample after saturation with a respectable level of accuracy. The proposed method is evaluated by MATLAB and PSCAD software. The effectiveness of the suggested method for different fault types under varied situations has been proved. The simulation outcome confirms the method’s high accuracy concerning the unusual system conditions in the presence of CT saturation.

Application of Discrete Wavelet Transform and Chebyshev Neural Network for Differential Protection of Indirect Symmetrical Phase Shift Transformer

The Indirect Symmetrical Phase Shift Transformer (ISPST) stands out from a power transformer due to its combination of electrically connected and magnetically coupled circuits. Hence in this work, an intelligent differential protection algorithm, based on Discrete Wavelet Transform (DWT) and Chebyshev Neural Network (ChNN), is proposed as main classifier to discriminate internal fault and inrush. Half cycle thee phase post fault differential current is considered for the proposed algorithm. PSCAD/EMTDC software is utilized to simulate different operating conditions of ISPST, resulting in the simulation of a significant amount of internal faults and inrush cases. The algorithm under consideration has undergone extensive evaluation across numerous cases, resulting in an accuracy rate exceeding 99%. The results indicate that the classifier based on DWT - ChNN yields extremely promising results, even when dealing with a noisy signal, current transformer (CT) saturation, and varying ISPST ratings. Superiority of the proposed algorithm is also compared with Multilayer Perceptron (MLP), Radial Basis Function Neural Network (RBFNN) and Probabilistic Neural Network (PNN) based approaches under the same conditions and it is found that proposed classifier is the most efficient and rapid among all alternative classifiers for the differential protection scheme of an ISPST under the considered conditions.

A new method for fault location in special parallel lines called “stitched lines”

Today, a special kind of parallel double-circuit line, designated "stitched lines," is employed in various transmission and sub-distribution networks in some countries, like Iran. In this type of unusual line, two circuits are connected at the beginning and end of the route and enter the high-voltage substations by a single line. Since on these lines there is no access to the current of each circuit separately, their protection, especially fault location, has faced a major challenge. Therefore, this article establishes a new method based on symmetrical components (positive sequence) to determine the location of the faults in the stitched lines. To scrutinize the performance of the proposed approach, comprehensive simulations have been run in the PSCAD/EMTDC software under a variety of different situations. The suggested method's accuracy has been established for a variety of fault locations and resistances. It has also been determined how the suggested approach performs when subjected to noise, current transformer saturation, arcing faults, transposition type, source impedance variation, and load changes. The obtained results show that the proposed approach is accurate under different scenarios, making it an excellent choice for practical applications.

Remanent flux detection method for a protection current transformer based on fluxgate theory

Protection current transformer (CT) saturation caused by the remanent flux will affect the performance of protective relays. The saturation can be suppressed by demagnetizing the iron core. Detecting remanent flux can make demagnetization more effective. This paper proposes a remanent flux detection method based on the fluxgate theory, which can effectively measure the magnitude and polarity of the remanent flux using the second harmonic of the current generated by a single-phase electronic inverter. The proposed method can detect the remanent flux without changing it, no matter whether the CT is connected to the power system or not, which means that this method can measure the remanent flux when the CT is under normal operating conditions. The effectiveness of this method is verified in EMTP-RV software, and the simulation results show that this method can detect the remanent flux with high accuracy.

FAULT DETECTION AND LOCATION BASED SVM FOR THREE PHASE TRANSMISSION LINES APPLYING POSITIVE SEQUENCE FAULT COMPONENTS

Transmission lines are an imperative element of the modern power systems. Any faults in them can cause an undesirable interruption in power supply. Precise analysis of these faults is important in-order to ensure an incessant supply of power. For this purpose, fault detection and classification are needed to clear any such faults and re-establish the system to maintain its normal operation. In this paper, a novel integrated approach of protective relaying with enhanced support vector machine algorithm has been adopted for detecting faults and its location estimation in long transmission line. The proposed scheme is successfully able to detect and classify different symmetrical and unsymmetrical faults along with some peculiar cases related to High Impedance Faults (HIF) and evolving faults, current transformer (CT) saturation/ capacitive voltage transformer (CVT) transient, close-in faults, swing condition, source strength variation, etc. The comparative analysis with recent proposed techniques declared the potentiality and robustness of the scheme

Relay algorithm for STATCOM compensated line using differential current ratio

Static synchronous compensators (STATCOMs) are used in the power transmission line to improve the voltage profile and stability. For a fault on the line, additional uneven reactive current from the compensator causes the maloperation of local data-based relaying schemes. In this work, using the current of both ends of the line, internal faults and faulty phases are identified by the ratio of both end’s current difference to the local one. Both the magnitude and angle of the ratio are utilized to enhance the dependability and security of the relay operation. The performance of the proposed technique is validated in Western System Coordinating Council (WSCC), a 9-bus system using data obtained from PSCAD. The authenticity of the proposed method is further validated using field data collected from a 400 kV shunt compensated line in the Indian power grid. The suggested strategy is resilient to changes in fault resistance, source impedance, fault location, current transformer saturation, various compensation levels, and high resistance faults (HRF). A comparison of the proposed Algorithm with existing methodologies demonstrates its superiority.

Transient current protection for transmission lines based on the Kalman filter measurement residual

This paper introduces a pilot protection method for two-terminal transmission lines based on the measurement residual of an extended Kalman filter designed to track alternate current signals. Transmission lines that interconnect generation plants to consumers are the primary equipment most susceptible to faults, and failing to isolate them correctly and promptly may lead to system collapse. In this context, the measurement residual allows for rapid fault identification and tripping. In addition, the proposed solution requires computing and communication resources typically available for pilot protection since it uses conventional sampling rates and has a low computational burden. This paper details the theory and application of the extended Kalman filter and the results of the proposed method when tested against different simulation scenarios. These scenarios were built on an extra-high voltage transmission system implemented in ATP/EMTP, varying fault impedance, inception angle, distance, phases involved, and fault type. It also presents a statistical analysis of these scenarios, including channel asymmetry, errors in the current transformers’ conversion rate, and noise. Besides, it describes an analysis of the proposed method regarding current transformer saturation, high impedance faults, zero-crossing faults, external breaker opening, and power-swing. Finally, it compares the solution with other algorithms in the literature. The results indicate that the proposed solution is fast, accurate, secure, and dependable.

Time domain differential protection scheme applied to power transformers

This paper presents a new differential protection scheme for power transformers based on Intrinsic Time-Scale Decomposition (ITD) and Ensemble of Bagged Tree (EBT) as a classifier. The ITD decomposes the input nonstationary signal into Proper Rotation Components (PRCs) and a monotonic trend signal. In the proposed scheme, statistical time-domain features extracted from the ITD output are fed to the EBT classifier, which classifies different events, including internal fault, internal fault combined with inrush current, different inrush currents (energizing transformer, sympathetic, and recovery inrush current), and external fault. The combination of ITD and EBT tools requires only a limited sample of post-fault data to protect the transformer. The proposed scheme is tested under various operating conditions to confirm its accuracy, and the effect of current transformer (CT) saturation on the scheme's performance is evaluated. The scheme is immune to noisy conditions and does not require transformer parameters. The power systems were simulated using PSCAD/EMTDC and MATLAB software.

Efficient practical method for differential protection of power transformer in the presence of the fault current limiters

AbstractThe algorithms of the present generation of practical differential relays are based on two methods. The first method is based on the ratio of the harmonic content of the differential current, and the second one is based on the length of the time interval between the zero‐crossing points of the differential current, called the gap‐detection method. However, these methods suffer from the installation of the fault current limiters (FCLs) in the power system and current transformer (CT) saturation phenomenon. This paper deals with a simple practical method for differential relays to secure their performance. In the suggested method, a classifying algorithm is used to categorize the input signal of the relay and then the best method of the present generation of differential relays is employed. By this simple decision, the method takes the advantage of harmonic‐based and gap‐detection methods, while avoiding their drawbacks. To prove the robustness of the suggested method, a test bench with a resistive solid‐state fault current limiter (SSFCL) is implemented and examined in different situations. The results validate the consistency and the accuracy of the modified technique not only in the absence and the presence of the FCL but in the case of CT 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.

Three-Terminal Lines Fault Location Using Two Main Terminals Data in the Presence of Renewable Energy Sources

Penetration of renewable energy sources (RESs) in power systems is increased considerably and fault location algorithms face considerable problems with the presence of RESs. Also, the third terminal of three-terminal lines is expanded as a cost-effective solution to energize the remote areas of medium voltage (MV) systems, while its data may not be measured and easily available. In addition, in cases where this data is obtainable, due to the excessive harmonics of the inverter-based resources (IBRs) in that terminal, the measured data includes high error. Therefore, providing a method for fault location in three-terminal lines in the presence of RESs is challenging. This paper proposes an accurate method to identify the fault location on these lines incorporating RESs without requiring the third terminal data. Due to current transformers saturation and transient response of capacitive voltage transformers, the fault location based on the faulted phase data contains significant errors. The proposed method combines both the faulty and healthy phases data to improve the accuracy of fault location. Its performance is evaluated on a MV system for different scenarios including various fault resistances, locations and types, and third terminal integration of RESs. The obtained results confirm superiority of the proposed method.

Analysis of characteristics of rail transit stray current and saturation mechanism of current transformer

Abstract The DC bias may affect the transient transfer characteristics of the current transformer (CT), threatening the correct action of the relay protection and the safe operation of the power system. Compared with the high voltage direct current (HVDC) transmission in the unipolar-earth loop operation mode and geomagnetically induced current (GIC), the amplitude of the stray current is smaller, and the randomness and fluctuation are larger and accompanied by sudden changes. Combining the characteristics of stray current and the CT equivalent model considering the eddy current loss of the iron core, the mechanism of local transient saturation under the influence of bias magnetization is explained, and the CT saturation phenomenon caused by stray current and its effect on line distance protection are simulated and analyzed. The research shows that the influence of low amplitude and high duration of stray current will make the magnetic flux of CT grow and affect the transmission of steady-state and transient-state so that the measurement impedance appears amplitude-phase shift, which leads to under-range rejection of distance protection.

Waveform dissimilarity factor-based protection for main transformers in wind farms

Current differential protection (CDP) is widely used as main protection for transformers due to its high reliability and selectivity. Owing to non-fundamental frequency current, magnetizing inrush and current transformer (CT) saturation, CDP may undergo slow operating speed when the internal fault occurs. When the external fault occurs, CDP may false operate. Furthermore, given the disadvantage of Hausdorff distance being extremely sensitive to abnormal data, a new metric that reveals the dissimilarity degree of two waveforms is presented, namely waveform dissimilarity factor (WDF). WDF has inherent immunity to abnormal data. Subsequently, WDF-based protection for main transformer is proposed herein. In order to reduce the adverse effects of magnetizing inrush and CT saturation and accurately identify internal faults, the reward and punishment mechanism is designed. The protection principle is elaborated and its operating characteristics are analyzed under various conditions. Finally, by constructing the DFIG-based wind farm, PSCAD is used to verify the advantages of the novel protection algorithm based on WDF. Its performance is widely assessed in various scenarios in detail, including magnetizing inrushes, minor and server internal faults, inter-turn fault, turn-to-ground fault, internal fault with CT saturation and external fault with CT saturation, data loss, abnormal data, and CT error. The results show that the novel protection scheme has the characteristics of fast, secure, and robust.