Electrical Faults Research Articles

Gassing Tendency of Fresh and Aged Mineral Oil and Ester Fluids under Electrical and Thermal Fault Conditions

Operational factors are known to affect the health of an in-service power transformer and to reduce the capabilities and readiness for energy transmission and distribution. Hence, it is important to understand the degradation rate and corresponding behavioral aspects of different insulating fluids under various fault conditions. In this article, the behavior of mineral oil and two environmentally friendly fluids (a synthetic and a natural ester) are reported under arcing, partial discharges, and thermal fault conditions. Arcing, partial discharges and thermal faults are simulated by 100 repeated breakdowns, top oil electrical discharge of 9 kV for five hours, and local hotspots respectively by using different laboratory-based setups. Some physicochemical properties along with the gassing tendency of fresh and aged insulating liquids are investigated after the different fault conditions. UV spectroscopy and turbidity measurements are used to report the degradation behavior and dissolved gas analysis is used to understand the gassing tendency. The changes in the degradation rate of oil under the influence of various faults and the corresponding dissolved gasses generated are analyzed. The fault gas generations are diagnosed by Duval’s triangle and pentagon methods for mineral and non-mineral oils. It is inferred that; the gassing tendency of the dielectric fluids evolve with respect to the degradation rate and is dependent on the intensity and type of fault.

Effect of Data Normalization on Accuracy and Error of Fault Classification for an Electrical Distribution System

ABSTRACT Unpredictable occurrence of electrical faults on a distribution system leads to power outages for electricity consumers. This makes accurate detection and classification of faults an important task. To isolate faulty sections, output of artificial intelligence (AI)based fault classifier is used to design optimum protection schemes for distribution systems. To enhance classifier’s performance, digital signal processing techniques like discrete wavelet transform (DWT) are implemented to extract features from fault signals. If extracted features have large variations, normalization is required to convert them on a common scale. Here, the error and accuracy in classification of line to line fault current (L-L fault) is evaluated if z-score normalized and not normalized inputs are used for backpropagation neural network (BPNN) classifier. Experiments are conducted on IEEE 13 bus test distribution system simulated in MATLAB. Results clearly show significant increase in accuracy of fault classification with considerable reduction in error to classify the faults due to normalization of input data.

Fault Diagnosis and Maintenance Skills of Electrical Control System

With the advancement of industry and technology and the support of advanced technological processes, electrical control system has undergone tremendous changes. Various technologies constitute advanced technology, and their integration into electrical control system enables industrial business to be developed better. However, due to the late start of industrialization in China, there are still inadequate researches, and it is not mature enough to deal with faults in electrical control. The author first introduces the relevant content of electrical control system, then briefly introduces the electrical fault inspection and diagnosis technology, and finally discusses how to repair the electrical control system.

Research on detection method for aviation bus based on electrical characteristics

Based on the current situation of aviation bus detection, this paper analyzes the application limitations and shortcomings of existing detection methods. On this basis, an improved detection method in frequency-domain for two common aviation buses with different structures based on TDR technology is designed, and the detection of hard faults is used as an example to explain the detection strategy, application difficulties and solutions. Besides, the detection of soft faults for aviation bus are emphatically studied based on this method. The experimental results show that the scheme has high feasibility and good diagnostic accuracy, which provides an important reference value in engineering for reducing the difficulty and improving the efficiency of electrical fault detection for aviation bus.

Arc Fault Protection and Detection

Arc faults in electric circuits are recognized as an important cause of fire. The first Arc Fault Circuit Interrupter (AFCI) has been patented in 1980 in the United States. AFCI is a device designed to detect electric arc faults which was prescribed for use by the National Electric Code (NEC, US Wiring Regulation) in January 2008. The NEC describes it as ‘A device intended to provide protection from the effects of arc faults by recognizing characteristics unique to arcing and by functioning to de-energize the circuit when an arc fault is detected’. At the beginning of 2012 the Arc Fault Detection Device (AFDD) began to be introduced into the IEC world, culminating in the publication of Technical Product Standards IEC 62606 ' in August 2013, which sets out the requirements for arc fault protection devices. This paper underlines the importance of preventing electrical fires by using the new technology of AFDDs, which largely extend the protection offered by traditional circuit breakers like MCBs and RCDs. Product standard IEC 62606 and functional tests are reviewed, the functioning of AFDDs is explained and a method to design robust algorithms for arc fault detection is proposed.

Response Mechanism of DFIG to Transient Voltage Disturbance Under Commutation Failure of LCC-HVDC System

Commutation failure is one of the common faults in the line commutated converter high voltage direct current (LCC-HVDC) transmission system, which will lead to a transient voltage disturbance with the characteristic of “decrease first and then increase” at the feed end. Such a transient voltage may cause severe dynamic responses on the wind generator adjacent to the converter station, resulting in the tripping of large-scale wind turbines and even cascading failure. By analyzing the principle of the transient voltage, this paper investigates the response mechanism of doubly-fed induction generator (DFIG), involving the variation of electrical parameters and fault ride through (FRT) ability. Further verifications through simulations and experiments prove that under the disturbance of commutation failure, DFIG may suffer greater transient shocks compared to a single sag or swell disturbance event. Finally, some suggestions are put forward to mitigate the transient voltage and improve the transient response of DFIG.

A Survey of Fault Location Techniques for Distribution Networks

Since recent societies become more hooked into electricity, a higher level of power supply continuity is required from power systems. The expansion of those systems makes them liable to electrical faults and several failures are raised due to totally different causes. As a result of these failures, the faulty element ought to be disconnected and isolated as soon as possible to reduce the damage and remove the emergency state from the whole system. Power quality considerations impose the grid to spot the faulted area as rapidly as doable, which forces utility operators in speeding up fault detection and system recovery and subsequently decreasing blackout time and pertinent costs. All these conditions have raised incredible significances about investigating methods and techniques used for fast detecting of faulted area, thus this matter needs to be pulled in broad consideration among researchers in power systems. In this paper, a comparative environment classifies and surveys a wide number of fault location procedures for distribution networks. The paper can be considered as a guide for operating engineers and researchers to settle on the foremost viable plausibility backed their existing framework and necessities

Parametric indicators for partial shading and fault prediction in photovoltaic arrays with various interconnection topologies

Photovoltaic arrays are mainly installed to generate maximum power and serve the load demand. However, the arrays are susceptible to various unpredictable scenarios such as partial shading and electrical faults that reduce the overall performance and result in serious power loss, hotspot formation, and severe damage to the modules. So, partial shading and fault detection algorithms are considered to be an important constituent to avoid unwanted power loss and system failures. Most of the algorithms use the voltage and current variation approach as detecting indicators for shading and faults. However, the array voltage and current can also vary due to certain other factors such as module temperature difference that result in reliability reduction due to false detection. In this paper, the sensitivity of various widely used array topologies to partial shading and electrical faults have been studied using various electrical parametric indicators. The variability of these indicators to shading and faults has been studied for determining the most relevant indicators that can be used for shade and faults detection in all array topologies. Also, the topologies have been studied using the characteristics curves, power generation, and mismatch losses to determine the most fault-tolerant topologies. The entire study has been performed in the MATLAB/Simulink environment and validated using experimental analysis. It has been found that the indicators largely varies to the shading/faults in the arrays and differs for different topologies and can be used to detect/predict faults. Also, it has been found that during minimum (10%) and maximum (90%) system shading, the parallel topology generated higher power nearly equal to 88.95% and 19.48% of the unshaded scenario respectively. However, during 90% system fault, all the topologies generated nearly equal power i.e. 11.27% of the no-fault scenario.

Generation of Mechanical Frequency Related Harmonics in the Stray Flux Spectra of Induction Motors Suffering From Rotor Electrical Faults

Lately, the monitoring and analysis of the induction motor stray flux has been a modern trend and significant research work was accomplished. Most papers have focused on the monitoring of rotor electrical faults around the fundamental stray flux signature, imitating in this way the traditional motor current signature analysis (MCSA). However, such signatures may still have some disadvantages leading to false alarms. This is the motivation behind the use of alternative signatures, such as in this particular case and the mechanical frequency. The existence of the mechanical frequency in the stator current is still the best signature for detection of the mixed rotor eccentricity fault and load imbalances. Even healthy motors present this harmonic due to some low-level inherent eccentricity and inherent load oscillations. Despite that, it will be shown for the first time in this article that the mechanical frequency associated harmonics in the stray flux is possible to originate purely from rotor electrical faults. Those signatures present significant sensitivity to the broken bar fault severity. Moreover, they are advantageous for low load operation compared to traditional signatures. Finally, the sidebands of the mechanical frequency related harmonics are very sensitive to the broken rotor bar fault while quite immune to the number of the rotor bars.

Voltage-Based Current-Compensation Converter Control for Power Electronic Interfaced Distribution Networks in Future Aircraft

Superconductors have a potential application in future turboelectric distributed propulsion (TeDP) aircraft and present significant new challenges for protection system design. Electrical faults and cooling system failures can lead to temperature rises within a superconducting distribution network, which necessitates a reduction or temporary curtailment of current to loads to prevent thermal runaway occurring within the cables. This scenario is undesirable in TeDP aircraft applications where the loads may be flight-critical propulsion motors. This article proposes a power management and control method that exploits the fast-acting measurement and response capabilities of the power electronic interfaces within the distribution network to maximize current supply to critical loads, reducing the impact of a temperature rise event in the superconducting distribution network. This new algorithm uses the detection of a resistive voltage in combination with a model-based controller that estimates the operating temperature of the affected superconducting cable to adapt the output current limit of the associated power electronic converter. To demonstrate the effectiveness of this method and its impact on wider system stability, the algorithm is applied to a simulated voltage-source converter supplied aircraft dc superconducting distribution network with representative propulsion motor loads.

An automatic algorithm of identifying vulnerable spots of internet data center power systems based on reinforcement learning

The internet data center (IDC) power system provides power guarantee for cloud computing and other information services, so its importance is self-evident. However, the occurrence time of malignant destructive events such as lightning strikes, errors in operation and cyber-attacks is unpredictable. But the loss can be minimized by formulating coping strategies in advance. So, identifying the vulnerable spots of the IDC power system come to be the key to guarantee the normal operation of information systems. Generally, the IDC power network can be modelled as a graph G, and then, the methods of finding nodes’ centrality can be applied to analyse the vulnerability. By our experience, it is not the best approach.Unlike the previous approaches, we do not solve the issue as the traditional graph problem. Instead, we fully utilize the characteristics of the IDC power network and apply reinforcement learning techniques to identify the vulnerability of the IDC power network. To our best knowledge, it is the first applying of artificial intelligence in traditional IDC power network.In this article, we propose PFEM, a parallel fault evolution model for the IDC power network, which can accelerate the process of electrical fault evolution. Moreover, we designed an algorithm which can automatically find the vulnerable spots of the IDC power network.The experiment on a real IDC power network demonstrate that the impact of vulnerable devices derived from our proposed algorithm after failure is about 5% higher than that of other algorithms, and tripping single-digit electrical devices of the IDC power system with our proposed algorithm will lead to loss of all loads.

Finite Element Modelling of Big Turbo-Generator Rotor Vibrations using Newmark-beta Integration Method

In this paper big turbo-generator rotor vibrations are simulated for various electrical faults. Newmark-beta method is used to simulate the vibrations at various critical sections of the rotor. Rotor is modelled using finite element method with solid, hollow and tapered elements. Torque in the generator during the course of electrical faults is modelled using dq0 formulation and solved in MATLAB using 4th order predictor-corrector method. Line to ground (L-G), line to line (L-L), three phase (L-L-L) and asynchronization faults are simulated for 300msec. The torsional vibrations in rotor at critical section is found to be most severe during three phase fault followed by mal-synchronization fault followed by the line to line fault followed by line to ground fault.

A Novel Configuration for Resistive SFCL with bifilar 2G tapes

Electrical faults on medium voltage electric power distribution systems can damage transformers. This fact motivated an R&D project in Brazil to study Fault Current Limiters for a utility. In this context, innovative design with a bifilar winding was developed for the present work, aiming to reduce self-inductance and to improve cooling rate. Long length second-generation superconducting tapes were used to build the prototype, which was constructed on a fiber-glass base. The prototype module has been tested at low voltage levels. The nominal operation, fault current limitation and recovery time have been examined for prospective currents of 2700 A and reduction of about 90 % in the current level. Due to fast recovery time and good heat exchange, the proposed topology has potential to be applied in a full-scale prototype.

New Method for OC Relay Coordination

Protection relays design and manufacture have arrived to a new level of advancement; hence, numerical relays have appeared recently. They combine all the functions of monitoring, control, and protection in one device. Also these relays have the ability to communicate with each other to share statuses and orders using GOOSE (generic object‐oriented substation events) messages based on communication protocols such as IEC61850. In this paper, a proposed method for overcurrent (OC) relay coordination has been introduced based on numerical relay features of several setting groups and communication capability. This work supposes that the coordination between feeder, bus section, and incomer protection relays, in a substation of single busbar configuration with bus sectionalizer (i.e., bus section), depends on the status of the bus section circuit breaker (CB) as a criterion for determining active relay setting group, to achieve a faster tripping action. ETAP has been used as a simulation software environment. And the simulation results show the advantages of the proposed method in reducing the time needed by the relay to clear the electrical fault. Siemens SIPROTEC series have been used as an example of numerical relays, specifically 7SJ64 as OC relay, which exists in the ETAP library.

Adsorption and gas-sensing properties of Pt2–GaNNTs for SF6 decomposition products

Partial electric discharge faults in gas-insulated switchgear (GIS) seriously affect the operational stability of power systems. In this study, H2S, SO2, SO2F2, and SOF2 were selected as characteristic SF6 decomposition products to characterize the partial electric discharge faults in a GIS. Pt cluster-modified gallium nitride nanotubes (Pt2–GaNNTs) were selected as the gas-sensing material to study their adsorption and gas-sensing performance for SF6 decomposition products H2S, SO2, SO2F2, and SOF2. Calculation results showed that Pt2 clusters presented stable doping structures on GaNNTs that greatly enhanced the surface activity for gas adsorption. The adsorption structures, adsorption energy, charge transfer, energy band, density of states, and molecular orbit were analyzed on the basis of density functional theory. Gas molecules formed stable structures on the surfaces of Pt2–GaNNTs through chemical adsorption. The order of adsorption ability was SO2 > H2S > SOF2 > SO2F2, and that of gas-sensing ability was SOF2 > SO2 > H2S > SO2F2. In this article, a new method to detect the partial electric discharge in GIS is proposed. The proposed method helps enhance the running stability of GIS.

Iron Prototype for Domestic Safety with Green Technology

Electrical fault is one of the causes of fires, and its potential hazard is increasing as more electrical appliances were found in each household unit nowadays. This is due to the number of fire cases arising from electrical appliances (i.e., iron), whereby the existing iron system unable to automatically turn off when idles for more than 30 second and missing green technology characteristics. Thus, the purpose of this project is to develop a smart iron prototype with security features and energy saving properties. The main objective of this project is to develop intelligent smart iron prototype using vibration and temperature sensor to get input for an automatic control. The Design Thinking Model was used to guide the development process through five phases namely; Empathize, Define, Ideate, Prototype and Test. The system was developed using Arduino Uno R3 microcontroller. The product testing indicated that the smart iron prototype has automatically supply cut off after 30 second without vibration and when the temperature exceeded 79 ° C to save energy. Therefore, application of this potential product could prevent major accident caused by iron and simultaneously save more energy when the iron left unattended, especially for the targeted users.

Analysis on Behavior Grounding Electrode Resistance base on Profiling Method

An earthing system or known as grounding system in an electrical installation where by the grounding system connects specific parts of that installation with the Earth’s conductive surface for safety and functional purposes. It is the process of transferring the immediate discharge with the aid of the low resistance wire of the electrical energy directly to the earth. It is really an important role playing in electrical system part as grounding system give protection during fault or lightning occur. In addition, grounding system also give protection for human electrical appliance and building from electrical shocks due to electrical fault or lighting occur. In this research will shows that to identify the best location to install the grounding electrode. This method is used on 10 x 10 meters which is 121 point will be investigated. The result of 0.3m, 0.6m, and 0.9m were analyzed using MATLAB software to produce profiling and shows the perfect location to install the Grounding system electrode.

Evaluation of Grounding System Values with Grid Type on 150 Kv in Batu Besar Substation, Batam

Generally, electrical fault occurs in substations, such as phase-to-ground short circuit. The fault currents flowing in Grounding System with Grid-Type can cause voltage gradient different on ground points around substation. The purpose of this study is to evaluate the Grounding System Values with Grid-Type whether meets standard, and protect somebody who is walking around substation or touching equipment stung of 150Kv electric in Batu-Besar Substation, Batam. Grounding System with Grid-Type needs to be evaluated every certain period to get Touch Voltage and Step Voltage that meet safety and security standard of IEEE Std 80-2013. The research method is to collect parameters ρ,ρs,hs,A,LT,h, which calculated using formula of Resistance Value, Touch Voltage, Step Voltage of Grounding System with Grid-Type. Then, analyzing and comparing of these data are performed based on results of calculation using the IEEE Std 80-2013. From results of this research, Resistance Value is 0.62Ω, 737.65V and 2,458.43V are Touch Voltage and Step Voltage of Grounding System Values with Grid-Type respectively, based on 0.5second interruption duration with somebody’s body weight of 50kg. The Evaluation results show that Grounding System Values with Grid-Type, meet the standard of IEEE Std 80-2013 for somebody who has weight 50kg in Batu-Besar Substation, Batam.

Electrical Faults Signals Restoring Based on Compressed Sensing Techniques

This research focuses on restoring signals caused by power failures in transmission lines using the basis pursuit, matching pursuit, and orthogonal matching pursuit sensing techniques. The original signal corresponds to the instantaneous current and voltage values of the electrical power system. The heuristic known as brute force is used to find the quasi-optimal number of atoms k in the original signal. Next, we search for the minimum number of samples known as m; this value is necessary to reconstruct the original signal from sparse and random samples. Once the values of k and m have been identified, the signal restoration is performed by sampling sparse and random data at other bus bars of the power electrical system. Basis pursuit allows recovering the original signal from 70% of the random samples of the same signal. The higher the number of samples, the longer the restoration times, approximately 12 s for recovering the entire signal. Matching pursuit allows recovering the same percentage, but with the lowest restoration time. Finally, orthogonal matching pursuit recovers a slightly lower percentage with a higher number of samples with a significant increase in its recovery time. Therefore, for real-time electrical fault signal restoration applications, the best selection will be matching pursuit due to the fact that it presents the lowest machine time, but requires more samples compared with orthogonal matching pursuit. Basis pursuit and orthogonal matching pursuit require fewer sparse and random samples despite the fact that these require a longer processing time for signal recovery. These two techniques can be used to reduce the volume of data that is stored by phasor measurement systems.

Intelligent diagnosis of petroleum equipment faults using a deep hybrid model

Performance assessment and timely failure detection of the electric submersible pump can reduce operation costs and maintenance in the oil and gas field. Features of equipment malfunction are changes in vibration signals. Evaluation of vibrations based on accelerometer sensors can detect failures and allows assessment of system failures. This paper proposes a reliable deep learning-based method for electric submersible pump faults detection. The frequency, time and spectral information of the vibrational signal are considered as input to the deep hybrid model. The spectral information includes the spectrogram obtained using the short-time Fourier transform and the scalogram as a result of the continuous wavelet transform and provides a detailed study of the vibration signal. The proposed approach is compared with k-nearest neighbors, support vector machines, logistic regression, and random forest. The experimental evaluation shows that the proposed deep hybrid model is superior to these machine learning methods, and can automatically and simultaneously detect failures of the electric submersible pump according to the vibration signal that is generated during system operation. The proposed approach gives good results and can help an expert in automatic diagnostics of equipment and several complex technical systems.