Digital Differential Protection Research Articles

Digital Differential Protection for $3\phi$ Solid-State Transformers

This article presents the development, implementation, and testing of a digital differential protection for three-phase (3φ) solid-state transformers (SSTs). The developed digital differential protection is designed to implement the ANSI 87 T protection function. The differential currents used by the developed protection are created by the dq0 components of the currents flowing in the high and low voltage sides of a 3φ SST. Internal faults are detected and identified using the energy contents of high-frequency subbands present in the dq0 differential currents. The desired high-frequency subbands are extracted using the phaselet transform that processes signals without sensitivity to nonstationary changes in their frequency and/or phases. Energy contents in the extracted high-frequency subbands allow accurate, fast, and reliable detection and identification of faults in any part of a 3φ SST. The proposed digital differential protection is implemented for performance testing using a laboratory 25-kVA 3φ SST. Performance results demonstrate accurate, fast, and reliable response to different fault and nonfault events. Furthermore, responses of the developed differential protection are found to be consistent regardless of the fault type, fault location, and/or loading level.

Testing the Performance of a $dq0$ Phaselet Transform Based Digital Differential Protection for $3\phi$ Converter Transformers

This article presents and tests the performance of a digital differential protection for three-phase ( $3\phi$ ) converter transformers. The proposed digital differential protection is developed to comply with the ANSI 87T protection procedure. The presented protection is featured with fault detection based on the energy contents of the high-frequency subbands of the $d{-}q$ axis components of differential currents. Desired energy contents are extracted using the phaselet transform (PHT), which can process signals without sensitivity to the variations in their phase shifts. Energy contents of the high-frequency subbands offer accurate, fast, and reliable detection, and identification of internal faults in any part of a $3\phi$ converter transformer. The $d{-}q$ PHT-based digital differential protection is implemented for performance evaluation using different $3\phi$ converter transformers, when feeding controlled rectifier units. Performance results demonstrate accurate, fast, and reliable detection, and response to different types of fault, and nonfault events. Response features of the developed differential protection are complimented with simple implementation, reduced computations, and minor sensitivity to phase shifts, fault location, and loading levels.

Использование математической модели для настройки цифровой дифференциальной защиты трансформатора

Использование математической модели для настройки цифровой дифференциальной защиты трансформатора

A Novel Hybrid Machine Learning Classifier Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG based Wind Farms

The protection of intertie zone between wind farm and grid line is critical for stable and safe operation of both the grid line and wind farm in the event of fault within or outside the intertie zone. As a reliable source of renewable energy doubly fed induction generator (DFIG)-based wind farms have been increasingly integrated to the power grid over the last two decades. Nowadays with the enormous penetration of large-scale DFIG wind farms, the commonly used distance relays are no longer reliable due to their incapability of providing accurate impedance measurement during internal and external faults. Thus, it results in maloperation, false tripping, and/or delayed operation. Therefore, in this article a digital differential-based protective relay (DBPR) scheme is designed and developed to provide reliable protection for wind farm intertie zone. Additionally, a new Bayesian-based optimized support vector machine (SVM), as a supervised machine learning classifier approach, is developed to take into account both the dynamic behaviors of wind speed and the current measured by the current transformers. Thus, the proposed hybrid SVM-DBPR scheme can distinguish among the normal operation, internal and external faults correctly that helps to avoid any false tripping. In a laboratory environment the proposed DBPR is implemented in realtime using FPGA DE2-115 board equipped with Cyclone IV-E device (EP4CE115F29C7). It is found from both simulation and experimental results that the proposed hybrid SVM-DBPR is able to provide reliable, efficient, and robust protection for the intertie zone of wind farms with 97.5% accuracy rate.

An Artificial Neural Network Based Digital Differential Protection Scheme for Synchronous Generator Stator Winding Protection

This research depicts another artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection. The scheme incorporates two feedforward neural networks (FNNs). One ANN is utilized for flaw recognition and the other is utilized for inward deficiency

Combination of the Methods of symmetrical components and Double Entry to Increase the Reliability of Digital Differential Relay Protection

The method of symmetrical components is one of the main methods used to calculate asymmetric modes in electric power systems. To increase the reliability of digital differential relay protection in case of asymmetric faults, a combination of symmetric components and double entry methods is proposed. It is supposed to compile balance equations, to apply the theory of graphs and matrices, and the estimation of reliability indicators is carried out on the basis of the method of Markov chains. The obtained results allow to make a conclusion about the prospects of implementing a differential protection using the method of double entry and symmetrical components in the electrical networks.

Numerical busbar differential protection using generalised alpha plane

This study presents a digital differential busbar protection scheme based on generalised alpha plane approach which combines the benefits of percentage differential approach and two-restrain alpha plane approach. The proposed scheme utilises one cycle current transformer (CT) secondary current signals of all the bays connected to the busbar to map the operating points on a complex alpha plane. The proposed scheme has been evaluated by modelling an existing 400 kV Indian power generating station in PSCAD/EMTDC software package. The performance of the proposed scheme has been evaluated on large numbers of cases with wide variation in system and fault parameters. In order to verify authenticity of the proposed scheme, a laboratory prototype of the proposed busbar protection scheme has been developed. From the developed prototype, CT secondary current signals are captured during internal faults and external fault with CT saturation condition. Comparison between the simulation and prototype results clearly shows the effectiveness of the proposed scheme in terms of higher sensitivity during internal faults and better stability in case of external faults. The proposed protection scheme has a high response speed (around 5 ms) and hence can be considered on par with modern busbar protection schemes.

A Study of the Measurement Section of Digital Relay Protection Units

The problem of the electric power systems (EPS) relay protection (RP) units’ adjustment, which does not correspond to the real operation conditions, was considered. It was found that the availability of the integral analysis of the key elements of different design RP units under the particular operation conditions is the basic condition for the problem solving, which is provided by the application of adequate RP mathematical models and modern EPS motivating factors. The existing EPS and RP modeling methods and tools were analyzed. On the basis of the RP detailed modeling concept, developed by the authors, the mathematical models of the complete diagram of the measurement sections of the digital differential transformer protection were developed for different types of intermediate transformers and low frequency filters. The comparative numerical analysis of their influence on the primary input signal was performed, including the analysis with consideration of nonlinearity of the measuring current transformer excitation characteristic. The theoretical and practical studies, presented in the paper, permit to define the requirements imposed on RP mathematical models, which will be used in the further studies aimed at developing a method for RP adequate adjustment.

A COMPREHENSIVE MODEL FOR THE POWER TRANSFORMER DIGITAL DIFFERENTIAL PROTECTION FUNCTIONING RESEARCH

This article presents a comprehensive model for the two-winding power transformer digital differential protection functioning research. Considered comprehensive model is developed in MatLab-Simulink dynamic simulation environment with the help of SimPowerSystems component library and includes the following elements: power supply, three-phase power transformer, wye-connected current transformers and two-winding power transformer digital differential protection model. Each element of the presented model is described in the degree sufficient for its implementation in the dynamic simulation environment. Particular attention is paid to the digital signal processing principles and to the ways of differential and restraining currents forming of the considered comprehensive model main element – power transformer digital differential protection. With the help of this model the power transformer digital differential protection functioning was researched during internal and external faults: internal short-circuit, external short-circuit with and without current transformers saturation on the power transformer low-voltage side. Each experiment is illustrated with differential and restraining currents waveforms of the digital differential protection under research. Particular attention was paid to the digital protection functioning analysis during power transformer abnormal modes: overexcitation and inrush current condition. Typical current waveforms during these modes were showed and their harmonic content was investigated. The causes of these modes were analyzed in details. Digital differential protection blocking algorithms based on the harmonic content were considered. Drawbacks of theses algorithms were observed and the need of their further technical improvement was marked.

Digital differential protection technique of transmission line using instantaneous active current: theory, simulation and experiment

Current differential protection is widely used as the main protection in UHV/EHV (Ultra/Extra High Voltage) transmission lines with advantages of simple principle, high reliability and inherent phase-selection capacity. However, as the voltage level and line length increase, the performance of the current differential protection is severely restricted by distributed capacity current. Aimed at this problem, a rapid extraction method of single-phase active current is proposed in this paper. The method first uses single PLL (phase-locked loop) to track the phase of the corresponding fundamental voltage. Then the current signal is transformed from the abc static coordinate system to the pq rotating coordinate through transformation matrix. By filtering out the high-frequency AC signal on p axis with low-pass filter, the active current component remaining being in the same direction with voltage phase can be obtained. On this basis, a novel active current differential protection method is proposed, with the advantages of high sensitivity and strong capacity of enduring transition resistance without requirement for the acquisition of line impedance parameters. Finally, the proposed method is tested by a series of dynamic simulations through PSCAD and experiment. The simulation results show that the method has merits of effectiveness, robustness and rapidity.

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

This paper presents the analysis and development of a new digital differential protection for three phase (3φ ) power transformers. The proposed digital protection is based on extracting high frequency sub-band contents present in the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis components of the differential currents in order to identify internal faults. The desired high frequency sub-band contents are extracted using a single-stage wavelet packet transform (WPT), which offers parameterizing the energy in the high frequency sub-band contents using a finite number of coefficients. The WPT coefficients contain information that offer accurate, fast, and reliable detection and classification of transient disturbances, including magnetizing inrush and internal fault currents that may be experienced by 3φ power transformers. The <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> WPT-based digital differential protection is implemented for off-line performance evaluation using differential currents collected from a 5 kVA, 3φ, laboratory power transformer. Off-line test results demonstrate accurate, fast, and reliable detection, classification, and response to different types of fault and non-fault currents. These encouraging performances of the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> WPT-based digital differential protection are obtained with simple implementation, reduced computational burdens, and small memory requirements.

Power Transformer Differential Protection Based on Neural Network Principal Component Analysis, Harmonic Restraint and Park's Plots

This paper describes a new approach for power transformer differential protection which is based on the wave-shape recognition technique. An algorithm based on neural network principal component analysis (NNPCA) with back-propagation learning is proposed for digital differential protection of power transformer. The principal component analysis is used to preprocess the data from power system in order to eliminate redundant information and enhance hidden pattern of differential current to discriminate between internal faults from inrush and overexcitation conditions. This algorithm has been developed by considering optimal number of neurons in hidden layer and optimal number of neurons at output layer. The proposed algorithm makes use of ratio of voltage to frequency and amplitude of differential current for transformer operating condition detection. This paper presents a comparative study of power transformer differential protection algorithms based on harmonic restraint method, NNPCA, feed forward back propagation neural network (FFBPNN), space vector analysis of the differential signal, and their time characteristic shapes in Park’s plane. The algorithms are compared as to their speed of response, computational burden, and the capability to distinguish between a magnetizing inrush and power transformer internal fault. The mathematical basis for each algorithm is briefly described. All the algorithms are evaluated using simulation performed with PSCAD/EMTDC and MATLAB.

The Spectrum Comparison Technique of DWT for Discriminating between External Fault and Internal Fault in Power Transformer

Abstract – This paper proposes a technique for detecting and identifying internal winding fault of three-phase two-winding transformer. A spectrum component obtained from DWT of differential current is analyzed. A ratio between per unit differential current and per unit time is calculated and performed as comparison indicator in order to discriminate between internal fault condition and external fault condition. Various cases based on Thailand electricity transmission and distribution systems are studied to verify the validity of the proposed algorithm. Results show that the proposed technique has good accuracy to detect fault and to identify its position in the considered system. Keywords : Power transformer, External fault, Internal fault, Discrete wavelet transform 1. Introduction To guarantee safety and stability of power grid operating, a precise protection scheme is required. In the literature for fault detection, several decision algorithms have been developed to be employed in the protective relay [1-10]. Most of them have different solutions and techniques. An application of a finite impulse response ANN (FIRANN) as differential protection for a three-phase power transformer is proposed in [1]. In [2], the paper describes a new approach for transformer differential protection that ensures security for external faults, inrush, and over-excitation conditions and provides dependability for internal faults. A new relaying fuzzy logic algorithm to enhance the fault detection sensitivities of conventional techniques is proposed in [3]. The relaying algorithm consists of flux-differential current derivative curve, harmonic restraint, and percentage differential characteristic curve. In [4], a new algorithm based on processing differential current harmonics is proposed for digital differential protection of power transformers. This algorithm has been developed by considering different behavior of second harmonic components of the differential currents under fault and inrush current conditions. In [5], the paper describes a new approach for transformer differential protection that ensures security for external faults, inrush and over-excitation conditions and provides dependability for internal faults. In [6], a new algorithm based on processing differential current harmonics is proposed for digital differential protection of power transformers. This algorithm has been developed by considering different behaviors of second harmonic components of the differential currents under fault and inrush current conditions. In [7], a novel analysis of the currents arising during a turn-to-turn fault in transformer in which a winding is delta-connected is done, so that data acquisition pre- and post-fault conditions may lead to a correct diagnosis. The approach given in this paper is based on the analysis of current sequences which appear in the fault state, and mainly in the nature of a zero sequence current (ZSC) in a delta winding, which is thoroughly discussed. In [8], the paper addresses turn-to-turn faults in power transformer windings. A sensitive detection method for such faults is described. As a result, most research works are interested in only the effects from magnetizing inrush current and the discrimination between magnetizing inrush current and internal faults [1-8], and etc. In addition, wavelet transform has been reported in the literature [9]. The idea of application of wavelet transform to fault diagnosis is not new, and there is a number of research papers related to this idea [9-14]. The advantage of the wavelet transform is that the band of analysis can be fine adjusted so that high frequency components and low frequency components are detected precisely. Results from the wavelet transform are shown both in time domain and in frequency domain. In previous research works [12], an analysis of the spectrum of the transient current signal is performed in order to determine whether the current is a fault or a magnetizing inrush current. The approximated signal of DWT is then employed in the algorithm for a decision unit in the protection scheme.

Application of Discrete S-Transform for Differential Protection of Power Transformers

 Abstract—In this paper, a novel scheme based on Hyperbolic S-Transform (HST) is proposed for digital differential protection of power transformers. Hyperbolic S-transform is a powerful tool for non-stationary signal analysis in noisy conditions. Decision logic has been devised using extracted feature from differential currents due to transient phenomena in transformers. The HST of the differential current is calculated. Then, a Decision Index (DI) is calculated according to the spectral energy and standard deviation of the S-matrix. It is seen that DI values are different in the cases of internal faults and inrush currents. The scheme has been implemented in MATLAB environment and the inputs are differential currents derived from EMTP software. In order to simulate the internal turn to turn and turn to earth faults, the power transformer is modeled using 8×8 RL matrices obtained from the subroutine BCTRAN of EMTP software. The differential current signals are infected by noise and the robustness of the algorithm under noisy conditions is investigated.

MATLAB‐SIMULINK‐based simulation for digital differential relay protection of power transformer for educational purpose

AbstractDifferential protection was already applied toward the end of the 19th century and was one of the first protection systems ever used. Faults are detected by comparison of the currents flowing into and out of the protected plant item. As a result of the fast tripping with absolute selectivity, it is suited as main protection of all important items of plant. The article presents an approach to teaching relay laboratory using specially designed exercises that can be done using MATLAB‐SIMULINK. This article presents a MATLAB‐SIMULINK‐based technology to simulate differential relay for determining behavior of it during transformer internal fault protection. The results show that this simulation method can work properly and this design can be used for power system simulation in MATLAB‐SIMULINK. Evaluation of the simulation with more than 60 students is very positive in terms of their developing confidence in and understanding of this kind of relay operation. © 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 475–483, 2013

Improved transformer protection using probabilistic neural network and power differential method

This article presents a novel technique to distinguish between magnetizing inrush current and internal fault current of power transformer. An algorithm has been developed around the theme of the conventional differential protection method in which parallel combination of Probabilistic Neural Network (PNN) and Power Differential Protection (PDP) methods have been used. Both PNN and PDP method are independent of harmonic contents of differential current. The proposed algorithm is capable of detecting fault and its type in the eventuality of fault in the transformer. Moreover, the combination of PDP method with the PNN makes it capable to detect light internal faults for all ratings of transformers which improve the overall performance of digital differential protection scheme. For evaluation of presented algorithm, relaying signals of various operating conditions of power transformer, including internal faults, external faults, over-excitation and inrush conditions were obtained through modeling of transformer in PSCAD/EMTDC. The performance of proposed amalgamated technique (i.e. combined PNN and PDP method) is compared with the PNN, Feed Forward Back Propagation (FFBP) neural network and the conventional harmonic restraint methods. The results amply demonstrate the capability of the proposed algorithm in terms of accuracy and speed. The algorithm has been implemented in MATLAB. Keywords: Digital differential protection, Protective relaying, Probabilistic neural network, Active power relays, Power differential method.

A wavelet-based method to discriminate internal faults from inrush currents using correlation coefficient

In this paper a new method based on discrete wavelet transform and correlation coefficient is presented for digital differential protection. The algorithm includes offline and online operations. In offline operation, discrete wavelet transform is used to decompose typical three-phase differential currents for inrush current. Then an index is defined and computed. The index is based on the sum of the energy of detail coefficients at level 5 of three-phase differential currents at each half cycle. The online operation consists of capturing the three-phase differential currents using 10 kHz sampling rate, decomposing it by db1. Finally, the inrush current and internal fault is detected based on correlation coefficients of the computed index of pre-stored typical inrush current and a recorded indistinct signal. The effectiveness of the approach is tested using numerous inrush and internal fault currents. Simulations are used to confirm the aptness and the capability of the proposed method to discriminate inrush current from internal fault.

A Novel Wavelet-Based Algorithm for Discrimination of Internal Faults From Magnetizing Inrush Currents in Power Transformers

In this paper, a new algorithm based on processing differential current is proposed for digital differential protection of power transformers by considering different behaviors of the differential currents under fault and inrush current conditions. In this method, a criterion function is defined in terms of difference of amplitude of wavelet coefficients over a specific frequency band. The criterion function is then used for three phases, and internal faults are precisely discriminated from inrush current less than a quarter a cycle after the disturbance; this is one advantage of the method. Another advantage of the proposed method is that the fault detection algorithm does not depend on the selection of thresholds. The merit of this method is demonstrated by simulation of different faults and switching conditions on a power transformer using PSCAD/EMTDC software. Also the proposed algorithm is tested offline using data collected from a prototype laboratory three-phase power transformer. The test results show that the new algorithm is very quick and accurate

A new method for recognizing internal faults from inrush current conditions in digital differential protection of power transformers

In this paper, a new algorithm based on processing differential current harmonics is proposed for digital differential protection of power transformers. This algorithm has been developed by considering different behaviors of second harmonic components of the differential currents under fault and inrush current conditions. In the new method, a criterion function is defined in terms of time variation of second harmonic of differential current. By evaluating the sign of the criterion function for the three phases, the internal faults can be accurately recognized from inrush current conditions about half cycle after the occurrence of disturbance; this is one advantage of the method. Another advantage of the proposed method is that the fault detection algorithm does not depend on the selection of thresholds. The suitable performance of this method will be demonstrated by simulation of different faults and switching conditions on a power transformer. For this purpose, a small part of Iran power system involving a power transformer and the transmission lines on both sides of the transformer has been considered. To include effective factors on differential current components, the elements of this power system have been precisely modeled in PSCAD/EMTDC.

GPS synchronized digital current differential protection for transmission lines

Abstract This paper describes a newly developed digital current differential protection for transmission lines. The proposed protection is different from existing ones in two aspects: one is using GPS time information to implement synchronized sampling at all terminals of the protected line. Another is the application of new differential algorithm based on fault component instantaneous value. To evaluate the performance of the protection, both the EMTP simulation study on the new algorithm and the dynamic simulation test on the prototype of the protection are conducted. The test results have proved the correctness of the new algorithm and the feasibility of the protection scheme. This paper starts with brief introduction to overall scheme of the protection, then focuses on describing the principles of GPS based synchronized sampling and new differential algorithm. The simulation results are also presented.