Types Of Internal Faults Research Articles

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.

Differential Reactor Voltage Based Fault Detection and Classification for Smart DC Microgrid

The primary challenges in the implementation of differential protection techniques are Time Synchronization Error (TSE) due to communication delay and low sensitivity towards High Resistance Faults (HRFs). In this paper, a new technique utilizing the difference in voltage measured across the external reactors connected at opposite ends of the cable is proposed for fault detection and classification of HRFs in islanded and grid connected mode of operation of DC microgrid. Further, to overcome the challenges associated with TSE, which causes differential schemes to mal-operate, the proposed technique determines reactor voltage polarity at opposite ends of the cable to distinguish between internal and external faults. The proposed technique is tested for different types of internal faults and system transients such as external faults, load switching, generation uncertainties etc. to demonstrate sensitivity and accuracy of the proposed technique. Finally, a comparative analysis of the proposed technique is performed with the schemes reported in the literature, which confirms the fast fault detection, high sensitivity for internal HRFs, selectivity and stability of the proposed technique for different operating conditions.

FAULT LEVEL DETECTION OF A THREE PHASE INDUCTION MOTOR USING MATLAB SIMULINK

This paper present a MATLAB based fault level detection of a three phase induction motor. Because of their simple and durable structure, as well as low production costs, three phase induction motors are employed in a wide range of applications. When it is in use, it is vulnerable to damage due to the defects that may occur. Overcurrent, unbalanced, overvoltage, undervoltage, single phasing, are examples of faults. Induction motors are employed in a wide range of industrial applications. THD (Total harmonic distortion) is also a problem for electrical engineers as it leads to heavy power loss in AC induction motors. These losses in AC induction motors leads to excessive heating, which happens because of additional copper losses and iron losses (eddy current and hysteresis losses) in the stator winding, rotor circuit, and rotor laminations. This causes lots of electrical equipment failure in the plants. The proposed scheme is simulated using MATLAB Simulink. MATLAB simulation results show that the well trained protest scheme is able to detect all types of internal faults and THD at different location. Keywords: three phase induction motor, fault classification, Proteus environment, THD.

Protection of Three Phase Induction Motor Using Embedded System

This paper present a PIC microcontroller – based control system for the protection of a three phase induction motor. The use of microcontroller technology has enabled the design of energy efficient and cost effective reliable control systems for induction motors. Fault types of induction motor like unbalanced voltage, over voltage, under voltage, over current, phase failure, over heat and more considered in this work. Fault monitoring and diagnosis are performed using protest environment. Fault classification is achieved through the microcontroller which includes a program for fault classification. When the fault occurs, the microcontroller sends a signal to the interfaced digital relay to trip the motor circuit and another signal to an LCD to display the type of fault. The use of microcontroller reduce the response time of the protection system and make it more suitable for real time operation. The proposed protection scheme is simulated using MATLAB Simulink. MATLAB simulation results show that the well trained protest scheme is able to detect all types of internal faults at different locations. The microcontroller used in this work is the high performance enhanced flash PIC16F877A Microcontroller of microchip which has an on chip analogue to digital converter peripheral, among other features. Keywords: PIC microcontroller, three phase induction motor, fault classification, Proteus environment.

Research on fault characteristics and protection system of cascaded power electronic transformers

Power electronic transformers (PETs) play a pivotal role in AC/DC hybrid distribution networks. However, there are few studies on the protection of PET. The safety of PET is seriously threatened by various internal faults. In this paper, internal faults of PET are classified according to fault positions and fault forms. The characteristics and hazards of different types of internal faults are analyzed and compared with external faults. The impacts of grounding mode, control mode, power direction and load level are considered in fault analysis. Moreover, an integrated protection system is established for PET. The principle and criterion of each protection relay are proposed based on fault characteristics. The correctness and effectiveness of fault analysis results and protection principles are verified via simulation tests.

Mechanical Switch Based Adaptive Fault Ride-through Strategy for Power Quality Improvement Device

Cascaded H-bridge power quality improving device (PQID) has garnered extensive attention for its flexible electric energy conversion and fast voltage response. However, the failure rate of PQID is relatively high due to the use of large numbers of power electronic devices. This paper proposes a mechanical-switch based adaptive fault ride-through strategy for improving the operational stability and power supply reliability of PQID. According to the features of the topology and working principle of PQID, this paper summarized the types of internal faults and analyzed the characteristics of different types of faults. Based on the shortcomings of existing mechanical switches as a bypass method, corresponding adaptive fault ride-through strategies are proposed for different types of faults, and a comprehensive simulation test has been carried out. The results show that the proposed strategy can adaptively ride through unit faults and effectively improve the output waveform quality during the ride through time.

Creative conjugate based characteristics to detect the faulty part in the generator-transformer unit

This study presents an innovative protection method for the generator-transformer zone based on the conjugate concept of the positive sequence component. The traditional protection for such zone employs two relays which generally uses twelve CTs. The proposed method uses one protective relay and utilizes nine CTs (a protective relay and three CTs are saved). The conjugate based innovative method protects the generator and the transformer as one unit and identifies the faulted zone. Such conjugate based inventive protection is based on the building of two relations. The 1st relation is between an adaptive conjugate signal of the neutral-generator current and an adaptive conjugate signal of the generator-transformer current. The 2nd relation is between adaptive conjugate signals of both transformer sides. Various types of external and internal faults, CTs saturation conditions, power swing conditions, and generator startup conditions have been generated by simulating part of the IEEE 9 bus system in the ATP program. The results clearly display the worth of the proposed protection in detecting the various types of internal faults. Other than, the new scheme can accomplish sensible differentiation among generator faults, transformer winding faults, and external faults. What's more, it contributes to encouraging results in the cases of the CTs saturation, power swing, generator startup, generator startup with faults, and different fault parameters. It isn't affected by the type of connection of the transformer. The tripping signal to the generator will be sent in case of a fault inside the generator while the tripping signal to the transformer will be sent in case of the fault inside the transformer.

Improving the transformer thermal modeling by considering additional thermal points

Early detection of internal faults within the transformer reduces the outage and repair costs by planning the repair procedure according to the circumstances and prior to a catastrophic failure. Thermal faults are types of internal faults, which lead to high temperatures in the transformer causing accelerated aging of the insulation or its short-term degradation. Physical-thermal models can predict the temperature distribution within the transformer and detect its thermal faults. The accuracy of these models depends on heat transfer modeling, experimental factors, modeling elements, and estimation of transformer design-dependent parameters. This paper improves a physical-thermal model by considering extra thermal points in it. The model is applied to three distribution transformers with natural oil and air cooling systems. The accuracy of the model is demonstrated, and an algorithm for fault detection is also introduced. It is shown that considering the radiator thermal points in the model, enhances its accuracy in the calculation of top oil and radiator temperatures. Moreover, it turns the model to an evaluation tool for the temperature gradients on the transformer height measured in the thermography.

Novel Fault Detection and Localization Algorithm for Low-Voltage DC Microgrid

Accurate estimation of fault location is highly crucial for swift maintenance and early power restoration. Since faults in dc networks are time critical, this article proposes a new fault detection and localization scheme for a low-voltage direct current (LVdc) microgrid network. Low-resistance faults are detected by observing voltage across the inductor whereas high-resistance ground faults are identified by measuring ground current at the relay location. Thereafter, based on iterative method, fault location is estimated by comparing analytically derived fault current with the measured value of fault current. Genuineness of the suggested technique has been assessed by simulating various internal, external, and simultaneous faults on a typical LVdc microgrid network modeled in power system computer aided design/electromagnetic transients including dc (PSCAD/EMTDC) environment. The proposed method is capable of detecting and locating both low- and high-resistance dc faults without utilizing remote-end quantities. Subsequently, initial guess has minimal impact on the convergence and accuracy of the proposed algorithm. Comparative evaluation of the proposed technique with other techniques clearly proves its superiority in terms of better discrimination against external faults, rapid detection during internal faults, independency on the network topology, and higher accuracy for fault distance estimation against all types of internal faults.

Countermeasure to Prevent the Incorrect Blocking of Differential Protection Applied to Converter Transformers

Harmonic blocking is usually applied by converter transformer differential protection to prevent protection mal-operation during an inrush condition, but it may incorrectly block the protection during an internal fault. This paper first makes an in-depth analysis on factors that lead to differential protection failure to trip for converter transformer internal faults. The main factor responsible for the protection failure to trip is half-cycle saturation of the converter transformer core, which results from the dc component in the fault current. This suggests that harmonic blocking may not be suitable for differential protection of converter transformers to identify inrush conditions. In this regard, this paper proposes a novel method using mathematical morphology to effectively discriminate between the conditions caused by inrush and internal faults. This method implements the waveform symmetry criterion and improved morphological gradient criterion to distinguish between these two conditions. The effectiveness of the proposed method is evaluated based on extensive simulation, and the presented results show that the proposed method can ensure operation for all types of internal faults. Additionally, this method improves the accuracy of inrush identification, even in extreme cases, such as sympathetic inrush and inrush with current transformer saturation.

New protection scheme for power transformer based on superimposed differential current

This study presents a new power transformer protection scheme based on extraction of positive and negative sequence components of superimposed differential currents. Different types of internal faults, magnetising inrush, and over-excitation conditions have been generated by modelling in service power transformer of power transmission system of India using PSCAD/EMTDC software package. The simulation results clearly indicate the efficacy of the proposed scheme in detecting different types of internal faults like turn-to-turn, inter-winding, line-to-ground, line-to-line, and line-to-line-to-ground. Together, the proposed scheme is competent to achieve effective discrimination between various external events (over-excitation condition and various magnetising inrushes) and internal faults. Moreover, it provides equally promising results during current transformer (CT) saturation condition as well as for different connection and rating of the power transformer. Further, it remains stable during errors in the CT and tap change condition. Additionally, authenticity of the proposed scheme has been evaluated using internal fault and magnetising inrush data recorded in the real field. At the end, comparative assessment of the proposed scheme with the existing and conventional techniques clearly indicate its superiority in terms of better sensitivity for internal faults and higher stability during external events.

A reliable setting-free technique for power transformer protection based on wavelet transform

This paper presents a new methodology based on the analysis and monitoring of the discrete wavelet transform (DWT) detail coefficients (DetC) for internal fault conditions identification and discrimination in power transformers. The method extracts the characteristics and calculates the DetC signals levels variation through DWT decomposition for identification of transients. During internal faults the DetC present a sudden and high variation, different from what happens in other transients, allowing their discrimination. The proposed method was able to correctly identify the different types of internal faults in power transformers and additionally transient as inrush currents. The main novelty of the method are: (1) Intelligent data analysis and monitoring, without a threshold adjustment; (2) Fast identification of an internal fault conditions and high coverage of turn-to-turn faults; (3) Secutity during transients such as inrush currents, external faults and overexcitation; (4) Simplicity. The results show that the proposed method has potential for real application in power transformers protection.

Design and development of fault classification algorithm based on relevance vector machine for power transformer

Identification of faults within power transformers is the means of ensuring unit transformer protection. Existing relay maloperates during abnormalities such as magnetising inrush, CT saturation and high resistance internal fault condition. Therefore, it is essential to categorise the internal fault and external abnormality/fault in case of transformer protection. This study presents a new scheme, based on relevance vector machine (RVM) as a fault classifier. The developed algorithm is assessed by simulating various disorders on 345 MVA, 400/220 kV transformer in PSCAD/EMTDC software and also on prototype model with 2 kVA, 230/110 V multi-tapping transformer. One cycle post fault current signals are captured from primary and secondary to form feature vectors. These feature vectors are used as an input to RVM for classification of various test cases. Wide variation in system parameters and fault conditions are considered for test data generation and validation. The proposed scheme is compared with the support vector machine (SVM) and probabilistic neural network (PNN)-based techniques. The proposed scheme successfully discriminates various types of internal faults and external abnormalities in power transformer within a short time. The fault classification accuracy obtained by proposed RVM technique is more than 99% in comparison to SVM and PNN-based schemes.

Ultraviolet differential optical absorption spectrometry: quantitative analysis of the CS2 produced by SF6 decomposition

The occurrence of partial discharge or partial overthermal fault in sulfur hexafluoride (SF6)-insulated electrical equipment frequently causes SF6 and solid insulation materials to decompose into various products. One of the most characteristic products of this process is carbon disulfide (CS2). The internal fault type and severity of the fault in the insulation equipment can be detected through the accurate quantitative detection of CS2. A device for simultaneously determining and quantifying gaseous CS2 via ultraviolet differential optical absorption spectrometry is developed in this study. A Sym14 wavelet transform and fast Fourier transform (FFT) are applied to process the spectral data of the feature regions, namely 190 nm to 210 nm. The concentration of CS2 is determined, and the detection limit of the developed device is identified. A good linear relationship is observed between the characteristic peaks of FFT and the concentration of CS2 after the operational parameters are optimized. Along the light path at 600 mm, the average detection limit for CS2 is 8.65 ppb based on three times the standard deviation of the system noises. The proposed device, which exhibits high sensitivity and effective cost, addresses the urgent demand for the monitoring and diagnosis of SF6-insulated electrical equipment via online detection of trace CS2.

Modeling of Magnetizing Inrush and Internal Faults for Three-Phase Transformers

Among the most noticeable root causes of improper performance in power transformers, internal short circuit faults can be noted and if not quickly be identified and addressed in the accepted time interval, irrecoverable damages such as interruption or even collapse of the network connected to the power transformer would happen. In this contribution, three-phase transformer behaviors under magnetizing inrush, internal short circuit condition and their current values determination have been surveyed using electromagnetic coupling model approach and structural finite element method. Utilizing the definition of transformer in the form of multi-coil and their electromagnetic and electric couple, a three dimensional geometric model of transformer is developed which includes nonlinear characteristics of the transformer, different states of normal and under internal short circuit occurrence and the moment of magnetizing inrush creation are investigated. The comparison between obtained results of presented model simulation with the consequences of practical studies on a typical three phase transformer reveals that the proposed model has a reliable accuracy in detection and modelling the transformer behavior in normal conditions, magnetizing inrush and different types of internal faults. The proposed approach represents an accurate model of a three-phase transformer for protection aims.

Modeling of Magnetizing Inrush and Internal Faults for Three-phase Transformers

Among the most noticeable root causes of improper performance in power transformers, internal short circuit faults can be noted and if not quickly be identified and addressed in the accepted time interval, irrecoverable damages such as interruption or even collapse of the network connected to the power transformer would happen. In this contribution, three-phase transformer behaviors under magnetizing inrush, internal short circuit condition and their current values determination have been surveyed using electromagnetic coupling model approach and structural finite element method. Utilizing the definition of transformer in the form of multi-coil and their electromagnetic and electric couple, a three dimensional geometric model of transformer is developed which includes nonlinear characteristics of the transformer, different states of normal and under internal short circuit occurrence and the moment of magnetizing inrush creation are investigated. The comparison between obtained results of presented model simulation with the consequences of practical studies on a typical three phase transformer reveals that the proposed model has a reliable accuracy in detection and modelling the transformer behavior in normal conditions, magnetizing inrush and different types of internal faults. The proposed approach represents an accurate model of a three-phase transformer for protection aims.

Waveform feature monitoring scheme for transformer differential protection

We propose a new scheme for transformer differential protection. This scheme uses different characteristics of the differential currents waveforms (DCWs) under internal fault and magnetizing inrush current conditions. The scheme is based on choosing an appropriate feature of the waveform and monitoring it during the post-disturbance instants. For this purpose, the signal feature is quantified by a discrimination function (DF). Discrimination between internal faults and magnetizing inrush currents is carried out by tracking the signs of three decision-making functions (DMFs) computed from the DFs for three phases. We also present a new algorithm related to the general scheme. The algorithm is based on monitoring the second derivative sign of DCW. The results show that all types of internal faults, even those accompanied by the magnetizing inrush, can be correctly identified from the inrush conditions about half a cycle after the occurrence of a disturbance. Another advantage of the proposed method is that the fault detection algorithm does not depend on the selection of thresholds. Furthermore, the proposed algorithm does not require burdensome computations.

Modeling and Characterization of Transformers Internal Faults Using Finite Element and Discrete Wavelet Transforms

This paper investigates the behavior of three phase transformers with internal faults under sinusoidal and nonsinusoidal operating conditions. The terminal behavior of the transformer was investigated by coupling the finite element transformer's physical model with external electric circuit equations. Two types of internal faults were modeled turn-to-ground faults, and turn-to-turn faults with and without arcing. A discrete wavelet transforms (DWT) procedure was then used to extract the feature of the transformer fault currents. The key advantages of the DWT are its ability to provide a local representation of the current signal for normal and faulty modes, as well as its applicability to handle nonstationary fault signals. This characterization gives us an efficient way to design and evaluate detection algorithms for transformers internal faults and the system they operate in

A Wavelet Technique for Directional Protection for EHV Transmission Lines with Series Compensation

The author provides a novel directional protection scheme for transmission lines with series compensation capacitors based on travelling waves. The ability of wavelet transform techniques to focus on system transients provides an effective and reliable method for fault detection and classification. Therefore, wavelet transforms are applied to the three phase currents at both ends of the transmission line. Directions and magnitudes of spikes in the wavelet coefficients are used for this purpose. The scheme is able to detect all types of internal faults at different locations in front and back of the series capacitor, at different fault inception angles and at different fault resistances. It also determines the type of fault and detects the faulty phase(s). Furthermore, it can detect external faults and blocks tripping if they exist. The relay remains stable for normal conditions, as well as in the presence of nonfaulty normal transients. The protection scheme is tested by simulating faults using the MATLAB power system toolbox. Simulation results show the high accuracy, security, and dependability of the proposed scheme.

Studies for identification of the inrush based on improved correlation algorithm

A new scheme based on an improved correlation algorithm to distinguish between inrush and internal fault in the transformer is proposed. In this scheme, the current over one cycle of each phase is reorganized as a new measurand. Fault currents can be distinguished from the inrush current if the improved waveform correlation coefficient between the first half-cycle and the latter-half-cycle of the above measurand is over a threshold. Test results show that all types of internal faults, even those accompanied by the magnetizing inrush, can be correctly identified from the inrush with the proposed algorithm. Besides high security, this scheme has satisfactory sensitivity. In addition, this algorithm can be easily implemented in the real-time process.