Transformer Differential Protection Research Articles

A Framework to Avoid Maloperation of Transformer Differential Protection Under Geomagnetic Disturbances

A Framework to Avoid Maloperation of Transformer Differential Protection Under Geomagnetic Disturbances

Transformer Differential Protection During Geomagnetic Disturbances: A Hybrid Protection Scheme and Real-Time Validation Tests

Transformer Differential Protection During Geomagnetic Disturbances: A Hybrid Protection Scheme and Real-Time Validation Tests

A power transformer differential protection method based on variational mode decomposition and CNN‐BiLSTM techniques

AbstractPower transformers play a critical role in the performance of power systems. This equipment is costly due to significant copper and iron prices and manufacturing costs. Therefore, maintenance and protection of such equipment is essential. Despite its robust performance, maloperation of differential protection (DP) in transformers may cause operational challenges to power system operators. The differential relay may operate incorrectly after the transformer energization leads to an inrush current (IC) and the relay identifies the event as an internal fault, and consequently issues the trip command. The other case of maloperation includes, but not limited to, a moment when the current transformer saturates due to an external fault. In this paper, a novel approach for DP is proposed, that is based on signal processing methods. In this paper, variational mode decomposition (VMD) and the deep neural network are implemented by using the convolutional neural network (CNN) and bi‐directional long short‐term memory (BiLSTM) models. The VMD decomposes differential current signal (DCS) to intrinsic mode functions with corresponding narrow‐band property frequency spectrums, which provides more detailed information about signal characteristics in different frequency bands. At the next stage, an effective feature for the BiLSTM is extracted by the CNN with the convolutional layers to classify events and proper discrimination. Extensive simulations on a 500 MVA transformer in MATLAB demonstrate the effectiveness of the proposed protection approach to differentiate ICs from internal and external faults with 99.8% accuracy in less than 1/8th of a power cycle.

Interoperability Challenges in Multivendor IEC 61850 Devices for Parallel Power Transformer Differential Protection

Interoperability of GOOSE messages is essential for the proper operation of protection schemes such as the parallel power transformer (PTRF) differential protection scheme, especially when using multivendor IEC 61850 devices. GOOSE messages allow for fast and reliable communication between intelligent electronic devices (IEDs) and are based on Ethernet communication. To ensure the interoperability of GOOSE messages between multivendor devices, adherence to the IEC 61850 standard specifications is crucial. The standard defines the format and content of GOOSE messages, including the data object model, data types, and communication protocols. Third-party testing and certification programs can also ensure compliance with the standard and help guarantee interoperability between different vendors. Device conformance with these standards does not ensure interoperability when devices from various manufacturers are utilized. Interoperability is necessary between the relevant devices from various vendors to provide system power stability and protection. If multivendor device interoperability is achieved, power utilities will be able to utilize multivendor devices in substations. The study investigates and provides comprehensive methods for achieving IEC 61850 standard-based interoperability problems in parallel with PTRF’s current differential protection schemes between IEDs (SEL-487E and MiCOM-P645) produced by different vendors under fault conditions. In a lab-scale environment with RTDS for real-time simulation in Hardware-in-the-Loop (HIL), the designed technique is simulated and tested.

Improved scheme based on memory voltage for transformer differential protection considering the effects of PLL

AbstractThe phase‐locked loop (PLL) is a critical control module applied in the control system of renewable energy sources (RESs) to synchronize with the grid voltage. When a fault occurs, the dynamic response process of the PLL will generate a phase locking error, resulting in a mass of harmonic components in the fault current of the PV inverter, which further poses challenges to transformer differential protection. To address the challenges posed by the phase locking error in practical engineering applications, this paper proposes an improved scheme that uses a digital computer algorithm to record and store the pre‐fault voltage and introduces the limiting coefficient. Firstly, the memory voltage is used to eliminate the phase locking error of the PLL, thereby mitigating harmonic distortion in the fault current of the RESs and ensuring the reliability of the transformer differential protection. In addition, the limiting coefficient is introduced to eliminate the effect of the increased amplitude of the fault current caused by the memory voltage. The voltage reference value of the inverter is multiplied by an appropriate limiting coefficient k and then output to the physical system. Finally, the effectiveness of the proposed scheme is verified by MATLAB/Simulink simulation.

Effects of Sampled-Values Data Quality on Responses of Time-Frequency Based Digital Relays

Time-frequency based digital protective relays can offer several advantages of high accuracy, improved reliability, and fast response over other protective relays. These protective relays employ half-band digital finite impulse response (FIR) filters to process currents and/or voltages to extract fault signatures, which facilitate accurate detection and identification of fault events. Coefficients of the employed half-band digital FIR filters are determined by wavelet or phaselet functions. The signal processing part in a time-frequency based digital protective relay processes samples of measured currents and/or voltages. As a result, attention has to be paid to the measurement, digitization, and communication of current and voltage data. Power systems utilize the IEC 61850 standard to implement data communication between measurement, control, and protection devices. This paper assesses the impacts of the IEC 61850 sampled values on the accuracy and response speed of time-frequency based digital protective relays. The presented assessment is conducted for two sample cases; the transformer differential protection and arcing current fault detection and identification. Test results show that the accuracy and response speed of time-frequency based digital protective relays are maintained, when measured currents and voltages are communicated using the IEC 61850 sampled values.

Determination of modern reliability indicators of relay protection and automation devices

RELEVANCE. The reliability of power supply to consumers depends on the reliability of all elements of the power supply system, including relay protection and automation devices (RZiA). Knowing the current values of the reliability indicators of various devices makes it possible to take them into account when designing RPA, choosing more reliable devices, identifying shortcomings in RPA and performing work to eliminate them. THE PURPOSE. Due to the lack of open data on the current values of reliability indicators of relay protection and automation devices (RPA) of electric networks of 10-110 kV, the question of their determination on the example of power systems of various regions is relevant. METHODS. The authors present and analyze official statistical data on the number of emergency failures, false and correct actuations of relay protection and automation devices in the electric grid organization - branch of PJSC «Rosseti Center» – «Ore lenergo» for 2013-2021. RESULTS. In the course of the study, numerical values of the following reliability indicators of relay protection and automation devices were determined: the failure rate and the frequency of excessive triggering. Relayprotection and automation devices, for which reliability indicators have been determined, are used to implement arc protection, maximum current protection, automatic re-activation, differential protection of buses and transformer, transverse directional differential protection, gas protection of transformer, differential-phase protection. CONCLUSION. The values of the failure flow for different types of relays and microprocessor devices of the RPA are established, for example, for an electromechanical relay of the DZT-11 type used to implement differential protection of transformers with a higher voltage of 110 kV, the failure flow is 0,2 year-1/100 pcs., and the frequency of excessive triggering is 22,22 year-1/100 pcs. Conclusions are drawn about the need for measures to regulate the settings and maintenance of devices of various types.

A Data-Aided Power Transformer Differential Protection Without Inrush Blocking Module

When a slightly faulty transformer closes without load, the current waveform presents the coexistence of inrush and fault current. At this time, the inrush blocking module will block the relay, which may delay the removal of the slight fault and lead to more serious faults. To address this problem, this paper proposes a data-aided power transformer differential protection without inrush blocking module. The key to eliminating the negative influence of inrush current is to extract the fundamental component from the non-inrush part of the current waveform, which corresponds to the unsaturation period of the transformer core. Firstly, a data-aided module, namely an Attention module embedded Fully Convolutional Network (A-FCN), is built to distinguish the inrush and non-inrush parts of the current waveform. Then, a physical model of the current waveform is built for the non-inrush part, and the fundamental component is extracted by the nonlinear least square (NLS) algorithm. The proposed method can avoid the block of differential protections when inrush current occurs, which improves the sensitivity and rapidity of the relay, especially in the case of a weak internal fault hidden in inrush current. Finally, simulation and experimental data verify the effectiveness and generalization of the proposed method.

Cybersecurity Enhancement of Transformer Differential Protection

Abstract: The increasing use of information and communication technologies (ICT) in the operational environments of power grids has been essential for operators to improve the monitoring, maintenance, and control of power generation, transmission, and distribution; however, this has come at the expense of increasing the grid's exposure to cyber threats. This paper looks at cyberattack scenarios that target protective relays in substations, which can be the most important part of protecting power systems from abnormal conditions. The overall performance of the power grid could suffer significantly if the relays' operations are disrupted, possibly resulting in widespread blackouts. Utilizing the potential of machine learning to detect anomalous behavior in transformer differential protective relays, we investigate methods for improving substation cybersecurity. In order to find cyberattacks, the proposed method looks at operational technology (OT) data from the substation current transformers (CTs). Power frameworks recreation utilizing OPAL-RTHYPERSIM is utilized to create preparing informational collections, to simulate the cyberattacks and to evaluate the network safety enhancement capability of the proposed AI calculations. Terms in the index include differential protective relays, transformers, operational technology, cyber physical systems, and machine learning.

New Method of Transformer Differential Protection Based on Graph Fourier Transform

In order to enhance the anti-saturation capability of transformer differential protection, a new method based on graph Fourier transform is proposed. First, by analyzing the characteristics of the similarity of the differential protection of the side current and the eigenvector. Secondly, the graph Fourier transform calculates the spectral coefficient for the differential current diagram signal, and constructs the action component and braking component of the differential protection, which can more accurately and effectively identify the faults in the differential protection area, and significantly improves the anti-saturation ability. The dynamic imitation and engineering cases have proved that the new criterion has high sensitivity and maximum TA saturation ability compared to the current mode value and maximum braking methods widely used in the current engineering.

Impact of large-scale photovoltaic-energy storage power generation system access on differential protection of main transformer under symmetrical faults

The low voltage ride-through (LVRT) requirements demand large-scale photovoltaic (PV) power generation system remain connected to the grid during faults. It results in considerable impact on the characteristics of fault current. This paper combines charge-discharge characteristics of the energy storage (ES) with PV generation system to enhance the LVRT capability. Based on the inverter control strategy and specific LVRT requirements, fault current characteristics of the PV-ES power generation system is discussed in this paper. In order to analyze the fault characteristic, the fault current expression as three-phase short-circuit faults occurs on both sides of the main transformer is calculated. Furthermore, taking the winding connection of the transformer into account, the ratio of differential current to braking current is further derived to find out the factors influencing the performance of the transformer differential protection. It is found that factors influencing the transformer differential protection include the rated capacity of the PV-ES generation system, fault severity, the length of transmission line and so on. And as the rated capacity of the PV-ES power generation system increase, the transformer differential protection would experience reduced sensitivity or even do not trip. The findings of this paper can lay a foundation for further improvement of the transformer differential protection. The elaborate performance evaluation of transformer differential protection, including the operation condition of the second harmonic braking element, is presented and verified by simulation using MATLAB/Simulink.

Countermeasure to Prevent Transformer Differential Protection From False Operations

Countermeasure to Prevent Transformer Differential Protection From False Operations

An Approach to Performing Stability Analysis for Power Transformer Differential Protection: A Case Study

Differential protection normally detects short circuits and ground faults in the windings of a power transformer and its terminals. Inter-turn faults refer to flashovers among the electrodes that arise only in a similar type of physical winding. Inter-turn faults can be examined when the adequate sum of turns is served as short-circuited. In electrical protection, it is difficult to detect inter-turn faults. An inter-turn fault of small magnitude is based on the limited number of turns that resultantly provide a large quantity of current. Due to this reason, protection that comes from the differential scenario possesses a higher degree of sensitivity without causing unwanted operations during external faults. In this paper, a protection-based stability method is proposed whereby external voltages are applied at the low-voltage (LV) side of the transformer while keeping the high-voltage (HV) side short-circuited. This was conducted using a three-phase power transformer (rating: 100 MVA, 380 kV/13.8 kV) at SWCC Shoaiba Power Plant, Saudi Arabia. In this work, differential protection (87T) and high-impedance differential protection for HV-restricted earth faults (REFs) were verified by creating In-Zone and Out-Zone fault conditions to ensure current transformer (CT) circuits and tripping logic. All of the IEDs, protection, and control schemes involved were designed by ABB. This method verifies protection stability for power transformers by implementing differential protection (87T) and high-impedance restricted earth fault (64HV) schemes through creating In-Zone and Out-Zone fault conditions.

A Waveform-Based Approach for Transformer Differential Protection Under GIC Conditions

Harmonic blocking (HB)-based differential relays, generally employed in the transformer protection, are likely to fail to interrupt internal short-circuit faults that occur under geomagnetically induced current (GIC) conditions. This paper proposes a waveform-based approach that enhances the differential protection dependability under the GIC conditions by detecting the GIC and overriding the HB signals for the internal faults. A novel algorithm is developed for the GIC detection, which employs three-phase instantaneous differential current waveforms and recognizes a GIC condition if the waveforms are all asymmetric in one direction. The proposed waveform-based approach also utilizes trip request signals of the differential relay's fault detection module to unblock the relay for the internal faults during the GIC. The results show that the proposed waveform-based approach (i) can successfully unblock the differential protection for the internal faults under the GIC conditions, (ii) does not malfunction for the external faults during the GIC, (iii) discriminates transformer energization cases from the GIC conditions, and (iv) is immune to the measurement noise. The current transformer (CT) saturation is also considered in the studies. The proposed approach's effectiveness is verified for different transformer types, including three-phase and single-phase transformers.

Transformer differential protection scheme based on self‐adaptive biased characteristic curve and considering cross‐country faults

AbstractThe differential protection of transformers sometimes does not have reliable performance facing some faults and events such as saturation of current transformers (CTs) during internal and external faults, inrush currents, and cross‐country faults (CCFs). In this paper, a new transformer differential protection scheme based on the self‐adaptive biased characteristic curve and considering CCFs and various disturbances are used. First, the maximum overlap discrete wavelet transform (MODWT) was used to extract the superior characteristics of sampled differential current of the transformer at different levels. Then, by calculating the duty cycle (D) values of energy coefficients extracted in each periodicity by MATLAB software, a new self‐adaptive biased characteristic curve will be obtained in different operating conditions. Finally, the percentage differential protection operation is adjusted based on the new adaptive characteristic curve zones. Differential current sampling under different operating conditions was performed on a real three‐phase transformer in EMTP software. The simulation results show that the proposed adaptive differential protection scheme can accurately detect various faults and events occurring in the transformer and increase system reliability.

Experimentally Validated Extended Kalman Filter Approach for Geomagnetically Induced Current Measurement

Geomagnetically induced currents (GICs) are referred to as the quasi-dc current flows in power networks, driven by complex space weather-related phenomena. Such currents are a potential threat to the power delivery capability of electrical grids. To mitigate the detrimental impacts of GICs on critical infrastructures, the GICs should be monitored in power systems. Being inherently dc from the power frequency point of view, the components of GICs are, however, challenging and costly to monitor in ac power grids. This article puts forward a novel methodology for the real-time estimation of GICs in power transformers. Such aim is attained by means of an extended Kalman filter (EKF)-based approach, mounted on the nonlinear state-space model of the transformer, whose parameters can be derived from standard tests. The proposed EKF-based algorithm employs the available measurements for the transformer differential protection. The proposed approach, relying on the differential current, can properly deal with the external sources of interference like harmonic excitation and loading. The EKF-based estimator presented is validated by simulation and experimental data. The results verify the ability of the proposed approach to robustly estimate the GIC level during various operating conditions.

Advanced Transformer Differential Protection Under GIC Conditions

This paper presents an advanced differential protection scheme for protecting transformers during geomagnetic disturbance (GMD) conditions and the flow of geomagnetically induced current (GIC) in the transformer. In this study, the inaccuracy of the existing harmonic blocking (HB) methods of the differential protection is investigated under the GIC conditions. It is shown that there are scenarios in which the HB-based differential relays fail to clear the internal faults since they are blocked due to the GIC-related harmonic currents. By detecting both GIC conditions and internal short-circuit faults, a solution scheme is proposed which overrides the harmonic inhibition signals issued by the HB module and makes the differential relay capable of tripping the transformer. Extensive time-domain simulations within the EMTP-RV verify the effectiveness of the proposed scheme in (i) unblocking the transformer differential protection for the internal faults during the GIC, (ii) preventing the malfunction for the external faults, (iii) distinguishing the transformer inrush and sympathetic inrush currents from the GIC conditions, and (iv) immunity to current transformer (CT) saturation. Furthermore, the simulation results prove that the differential protection equipped with the proposed approach outperforms the existing HB methods under the GIC conditions.

A new high-frequency-based method for the very fast differential protection of power transformers

A novel algorithm based on Teager energy operator (TEO) and hidden Markov model (HMM) is presented for the transformer differential protection. After detecting any increase in the amplitude of the transformer differential currents, it is needed to know if the over-current is because of an internal fault or an inrush phenomenon. In this paper, a combination of TEO and HMM is used to discriminate between the magnetizing inrush currents and the internal fault currents. TEO is used to extract high frequency components of the signal and present them as a curve, named as Teager output curve (TOC). Then TOC is used as the input for HMM. First, the HMM training process is implemented by an adequate number of the train signals and then, the unknown signals are identified by the testing process. Fault type identification is also performed by the use of TOC. TOC has a separated region for each of the three phases. TEO of the zero-sequence signal has a peak for the grounded and no peak for the un-grounded faults. Train and test signals are generated by the simulated system in PSCAD/EMTDC. Results by means of the simulated and experimental data show the robustness of the proposed algorithm.

Research on magnetizing inrush current of microgrid based on Grey identification

With the large-scale access of wind and light energy, the power system is gradually developing towards the micro grid with low inertia. AC microgrid often uses multiple parallel transformers to supply power to the load at the same time. In case of power failure due to a fault or maintenance, the parallel transformer needs to be powered on and closed without load to restore power supply. The parallel transformer is easier to saturate, the core remanence is higher, and the peak value of inrush current is larger, which has an impact on the stability of microgrid. It will also lead to misoperation of transformer differential protection and affect the safe and stable operation of power system. Therefore, a switching method of parallel transformer based on Grey recognition is proposed. Firstly, the generation mechanism of inrush current is analyzed theoretically, and then the waveform shape characteristics are analyzed. The grey whitening weight clustering method is used to identify the feature set to complete the magnetizing inrush current locking and ensure that the protection does not misoperate. Finally, the PSCAD simulation model is established to simulate the AC microgrid to verify the feasibility of this method.

Improvement of power transformer differential protection through detection and exploitation of the negative sequence currents

Introduction. Power transformers are the most important and the most expensive equipment used in transport and distribution of electrical energy. Their failure results in huge economic losses. Despite the great advances in the design of power equipment in recent years, the feeble link in the chain remains the insulation weakness of coil turns of the power transformer. The novelty of the proposed research consists in the development of a new procedure for diagnosing and localizing the occurrence of turn to turn short-circuits in the windings of three-phase power transformer. The main problems of the current differential relay are short circuits of one or more turns of a transformer winding. Hence a new approach using' the amplitude comparison between the negative sequence currents' is developed and a digital discriminator internal / external fault is applied to discriminate turn to turn faults among the other ones. The proposed procedure is based on the exploitation of the negative sequence currents. The purpose of using this new procedure is to identify small faults inside power transformer coils and to distinguish inner faults from the outer faults by using an ameliorate circuit. The method used in this paper is a novel algorithm which based on the comparison between the negative sequence current amplitudes and to calculate the corresponding phase angle shifts. The performance of the proposed procedure has been confirmed by MATLAB/Simulink environment. The results of simulation reveal the efficiency of the suggested procedure, and indicate that this procedure can provide fast and sensitive approach for detecting low level turn-to-turn faults.