Current Transformer Saturation Research Articles

Enhanced Kullback–Leibler Divergence Based Pilot Protection for Lines Connecting Battery Energy Storage Stations

In light of the challenges faced by existing protection methods when battery energy storage station (BESS) and various nonideal conditions emerge, enhanced Kullback–Leibler divergence-based time-domain pilot protection is put forward in this article. Given the discrepancy in current waveforms between internal and external faults, KLD is employed to quantify the degree of similarity between two current waveforms, enabling the accurate distinction between internal and external faults. To eliminate the asymmetry of KLD, improved KLD(IKLD) is introduced. Whereafter, a technique is proposed to convert the current sampling sequence into a probability distribution that can be utilized by IKLD. To counteract the negative influence of current transformer(CT) saturation on IKLD-based protection, the time-domain waveform features of summation current are adequately employed to develop an enhanced KLD(EKLD). Further, high and low thresholds are legitimately designed to ensure both dependability and security. The flowchart of EKLD-based pilot protection is described, and its effectiveness is extensively validated by variation in fault resistance, location, type and operating mode of BESS using PSCAD and a hardware-in-the-loop(HIL) testing platform. Additionally, proposed protection outclasses power frequency component-based current differential protection and some up-to-date presented time-domain protection methods.

Определение факта насыщения магнитопровода трансформатора тока на основе непрерывного измерения сопротивления цепи намагничивания

Saturation of electromagnetic current transformers in transient modes of operation of an electric power system can lead to incorrect operation of relay protection devices. One of the most promising directions to improve the stability of the operation of relay protection devices in such modes is digital correction of secondary current. Currently, effective methods have been developed to restore the secondary current based on determination of magnetic circuit saturation. However, the practical application of these methods is impossible due to the imperfection of existing methods of secondary current segmentation. Thus, it is urgent to develop a method to determine saturation for implementation of digital correction algorithms for electromagnetic current transformers. To solve the stated problem, methods of mathematical modeling of electrical circuits containing transformers and the small-disturbance theory have been used. Verification of the research results is carried out in the Matlab software package. A mathematical criterion is formulated to determine the saturation of the magnetic circuit of an electromagnetic current transformer based on the inductance of the magnetization circuit. A method of segmentation of the secondary current has been developed for the implementation of digital correction algorithms based on the proposed criterion. The effectiveness of the developed method to determine the saturation of the magnetic circuit of an electromagnetic current transformer using computational experiments in the Matlab software package is demonstrated. It is planned to verify the developed method using a physical model of an electromagnetic current transformer.

Complex plane based adaptive method for protection of series compensated transmission line using phasor measurement unit data

Though differential relays are preferred for the protection of series-compensated transmission line (SCTL), they may mal-operate during current inversion, high resistance internal faults and current infeed/outfeed situations. Therefore, a new protection scheme for SCTL using Phasor Measurement Unit data, that adaptively manages the operating region in the current ratio complex plane according to the percentage compensation level, is presented. Boundaries of the operating region are determined adaptively based on the estimated impedance value of the series compensation. Usefulness of the technique is confirmed by generating cases covering wide range of fault parameters, compensation level, and load angle on an existing 400 kV Indian SCTL using PSCAD software as well as through Hardware in Loop simulation employing the Real Time Digital Simulator. Reported outcomes reveal the ability of the suggested algorithm in sensing all types of internal faults. Its performance remains unaffected during current/voltage inversion, operation of MOV and/or airgap during high fault current conditions, current infeed/outfeed situation, and external fault with current transformer saturation condition. Impact of the presence of noise in the acquired signals is also analyzed. The suggested technique is applicable for SCTLs having different voltage levels and power flow conditions. The proposed method has higher responsiveness during high resistance internal faults up to 500 Ω and better steadiness during external faults compared to numerous prevailing methods.

Adaptability Analysis of Differential Protection for Output Transformers in Wind Power Plants

Abstract After large-scale integration of wind farms into the power grid, according to the requirements of the State Grid’s wind power grid connection operation guidelines, wind farms should have low-voltage ride-through capability. The short-circuit current of wind farms will have a significant impact on the identification of excitation inrush currents in the transformers sent out by the wind farms, and the saturation of current transformers will also have an impact on differential protection. Analysis shows that after the wind power is connected, the harmonic components contained in the fault current output by the wind farm will cause the second harmonic braking component to malfunction, and there is a risk of transformer differential protection rejecting operation. At the same time, it will make the current transformer more susceptible to saturation, and the saturation of TA will increase the differential current of the transformer, which may cause misoperation of the transformer differential protection.

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 Curve Fitting–Based Directional Protection of Transmission Lines Using Genetic Programing

In modern power systems, there is a growing need for protection techniques that are fast, precise, and stable to enhance the reliability and stability of power networks. This paper introduces an advanced technique for fault direction estimation that addresses key limitations in existing methods. Our proposed algorithm eliminates the dead‐zone issue, effectively handling both forward and reverse faults regardless of their location, including faults near relay regions. Using genetic programing (GP), we derive a closed‐form equation to drive the fault direction estimation algorithm, ensuring accurate and reliable results. The algorithm demonstrates exceptional speed and reliability in fault detection and direction estimation, even under challenging conditions such as current transformer (CT) saturation, power swing, and source strength variations. It is also insensitive to fault resistance and fault inception angle, increasing its robustness. A notable advantage of this algorithm is its efficiency at low sampling frequencies, making it highly adaptable for industrial applications and compatible with modern software and hardware requirements. We validated the algorithm through simulations on the electromagnetic transients program (EMTP‐RV) platform and with field data from the Manesht 230 kV substation in Ilam province, Iran. The results confirm the algorithm’s impressive speed and high reliability.

Current Transformer Saturation Detection Bases On Artificial Neural Networks

Protection and automation (PA) system is an integral part of electric power systems. The algorithms of the PA system operate based on the use of analysis of the electrical mode parameters - current and voltage - obtained from instrument transformers. As a rule, these transformers operate based on the electromagnetism laws. Operational experience shows that the current transformers (CT) core under fault conditions can be saturated. As a result, the shape of the measured current is distorted, which can lead to maloperation of the PA system. In this paper, a method for solving the problem of CT core saturation based on the use of artificial neural networks for classification problems is proposed. The saturation problem is reduced to a binary classification problem, a description of the synthesis of DATASET is given. Computational experiments were carried out for the cases of balanced (the number of CT modes with and without saturation are the same) and imbalanced classes. The experimental results show that the accuracy of the model can reach 99%.

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.