Arc Grounding Fault Identification Using Integrated Characteristics in the Power Grid

Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points.The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index,which leads to detection failure when the arc zero-off characteristic is short.To solve this problem,this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines.Firstly,the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied.After that,the convex hull,gradient product,and correlation coefficient index are used as the basic characteristic parameters to establish fault identification criteria.Then,the logistic regression algorithm is employed to deal with the reference samples,establish the machine discrimination model,and realize the discrimination of fault types.Finally,simulation test results and experimental results verify the accuracy of the proposed method.The comparison analysis shows that the proposed method has higher recognition accuracy,especially when the arc dissipation power is smaller than 2×10^(3) W,the zero-off period is not obvious.In conclusion,the proposed method expands the arc fault identification theory.

Research on Low Voltage Series Arc Fault Prediction Method Based on Multidimensional Time-Frequency Domain Characteristics

The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper.

Control method based on DRFNN sliding mode for multifunctional flexible multistate switch

To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Analysis of Fault Arc in High-Speed Switch Applied in Hybrid Circuit Breaker

The behavior of fault arc in a high-speed switch （HSS） has been studied theoretically and experimentally. A simplified HSS setup is designed to support this work. A two-dimensional arc model is developed to analyze the characteristics of fault arc based on magnetic-hydrodynamic （MHD） theory. The advantage of such a model is that the thermal transfer coefficient can be determined by depending on the numerical method alone. The influence of net emission coefficients （NEC） radiation model and P1 model on fault arc is analyzed in detail. Results show that NEC model predicts more radiation energy and less pressure rise without the re-absorption effect considered. As a consequence, P1 model is more suitable to calculate the pressure rise caused by fault arc. Finally, the pressure rise during longer arcing time for different arc currents is predicted.

Simulation of Fault Arc Based on Different Radiation Models in a Closed Tank

This paper focuses on the simulation of a fault arc in a closed tank based on the magneto-hydrodynamic （MHD） method, in which a comparative study of three radiation models, including net emission coefficients （NEC）, semi-empirical model based on NEC as well as the P1 model, is developed. The pressure rise calculated by the three radiation models are compared to the measured results. Particularly when the senti-empirical model is used, the effect of different boundary temperatures of the re-absorption layer in the semi-empirical model on pressure rise is concentrated on. The results show that the re-absorption effect in the low-temperature region affects radiation transfer of fault arcs evidently, and thus the internal pressure rise. Compared with the NEC model, P1 and the semi-empirical model with 0.7 〈 α 〈 0.83 are more suitable to calculate the pressure rise of the fault arc, where is an adjusted parameter involving the boundary temperature of the re-absorption region in the semi-empirical model.

Relation between the characteristics of strong earthquake activities in Chinese mainland and the Wenchuan earthquake

This paper studies the relations between the great Wenchuan earthquake and the active-quiet periodic characteristics of strong earthquakes, the rhythmic feature of great earthquakes, and the grouped spatial distribution of Ms8.0 earthquakes in Chinese mainland. We also studied the relation between the Wenchuan earthquake and the stepwise migration characteristics of Ms≥7.0 earthquakes on the North-South seismic belt, the features of the energy releasing acceleration in the active crustal blocks related to the Wenchuan earthquake and the relation between the Wenchuan earthquake and the so called second-arc fault zone. The results can be summarized as follows： ① the occurrence of the Wenchuan earthquake was consistent with the activequiet periodic characteristics of strong earthquakes; ② its occurrence is consistent with the features of grouped occurrence of Ms8.0 earthquakes and follows the 25 years rhythm （each circulation experiences the same time） of great earthquakes; ③ the Wenchuan Ms8.0 earthquake follows the well known stepwise migration feature of strong earthquakes on the North-South seismic belt; ④ the location where the Wenchuan Ms8.0 earthquake took place has an obvious consistency with the temporal and spatial characteristic of grouped activity of Ms≥7.0 strong earthquakes on the second-arc fault zone; ⑤ the second-arc fault zone is not only the lower boundary for earthquakes with more than 30 km focal depth, but also looks like a lower boundary for deep substance movement; and ⑥ there are obvious seismic accelerations nearby the Qaidam and Qiangtang active crustal blocks （the northern and southern neighbors of the Bayan Har active block, respectively）, which agrees with the GPS observation data.

Spectrum-Sensing Method for Arc Fault Detection in Direct Current System with Lithium Batteries

We mainly study the detection of arc faults in the direct current (DC) system of lithium battery energystorage power station. Lithium battery DC systems are widely used, but traditional DC protection devices areunable to achieve adequate protection of equipment and circuits. We build an experimental platform based onan energy storage power station with lithium batteries. Then, the data collection of normal current and arc-faultcurrent is completed under multiple conditions, and the waveforms of obvious and weak signals as the arc occursare presented. We analyze the principles and application range of several common spectrum-sensing methods andstudy the feasibility of applying them to the arc detection field. Finally, the covariance absolute value detectionalgorithm is selected, and the average value of the current is filtered out to make the algorithm adapt to the arcdetection field. The result shows that the detection probability in 500 sets of experimental data has reached 98%.

Improved Control Strategy for Carbonized Cable Preparation in Low-voltage Arc Fault Test

Outdated testing methods hinder the success rate of carbonized cable preparation in low-voltage arc fault tests,leading to incomplete tests and high failure rates.To address this issue,we finely categorized the preparation results of carbonized cable specimens by analyzing the experimental phenomena during the carbonization process and assessing the impact of high-voltage energization time on the outcomes,presenting a process control strategy aimed at optimizing the preparation results of carbonized cable specimens.This method utilizes three periodic moving algorithms(root-mean-square,average,and shoulder percentage)to classify the cable specimens into four preparation categories:open-circuit carbonization,under-carbonization,short-circuit carbonization,and successful carbonization.The high-voltage energization time during carbonization or secondary carbonization was adjusted to optimize the preparation of the carbonized cables by considering different discrimination outcomes.Finally,the proposed method was tested on a purpose-built carbonized cable experimental platform,which confirmed its effectiveness in differentiating the preparation outcomes of the carbonized cable specimens and improving the success rate of the carbonized cable preparation.The proposed method has significant potential for application in low-voltage arc fault test systems.

Intermittent Arc Fault Detection Based on Machine Learning in Resonant Grounding Distribution Systems

In resonant grounding systems,most single-phaseto-ground faults evolve from IAFs(Intermittent Arc Faults).Earlier detection of IAFs can facilitate fault avoidance.This work proposes a novel method based on machine learning for detecting IAFs in three steps.First,the feature of zero-sequence current is automatically extracted and selected by a newlydesigned FINET(“For IAFs,Neuron Elaboration Net”),instead of traditional feature selection based on time-frequency decomposition.Moreover,data of the zero-sequence current divided by different time windows are successively input into the trained FINET.A proposed PSF(principal-subordinate factor)analyses the results obtained from FINET to improve anti-interference in the mentioned IAF detection algorithm.Experiments using PSCAD/EMTDC software simulation data show the proposed method is feasible and highly adaptable.In addition,the detection result of on-site recorded data demonstrates the effectiveness of the proposed method in practical resonant grounding systems.

Identification of Transient and Permanent Faults

A new algorithm was developed for arcing fault detection based on high-frequency current transients analyzed with wavelet transforms to avoid automatic reclosing on permanent faults. The characteristics of arc currents during transient faults were investigated. The current curves of transient and permanent faults are quite similar since current variation from the fault arc is much less than the voltage variation. However, the fault current details are quite different because of the arc extinguishing and reigniting. Dyadic wavelet transforms were used to identify the current variation since wavelet transform has time-frequency localization ability. Many electric magnetic transient program (EMTP) simulations have verified the feasibility of the algorithm.

A fast arc fault detection method for AC solid state power controllers in MEA

Arc fault detection is desperately required in Solid State Power Controllers（SSPC） in addition to their fundamental functions because arcs will provoke growing harm and threat to aircraft safety. Experimental study has been done to obtain the faulted current data. In order to improve the detection speed and accuracy, two fast arc fault detection methods have been proposed in this paper with the analysis of only half cycle data. Both Fast Fourier Transform（FFT） and Wavelet Packets Decomposition（WPD） have been adopted to distinguish arc fault currents from normal operation currents. Analysis results show that Alternating Current（AC） arcs can be effectively and accurately detected with the proposed half cycle data based methods. Moreover,experimental verification results have also been provided.

Novel detection method for DC series arc faults by using morphological filtering

It has been known that DC arc faults pose a hazard in power electronics systems. Due to the fault current is lower than normal current load, series arc is more difficult to be discovered than parallel arc. The traditional methods of DC series arc faults detection have some disadvantages, such as large computation, long delay and easier influence by interferences. In this paper, a novel method with multi-scale morphological filtering was utilized for the fault detection of DC series arc. Compared to the tradition method, the proposed method is more simple and efficient. It was verified that it was convenient for field application of on-line monitoring and diagnosis with a good ability to prevent misjudgments from the environment interference.

A review on ignition characteristics of arc faults in wire system of aircraft

The development of aircraft electrification can improve energy utilization efficiency and reduce the green gas emissions,which is the future trend.However,aircraft electrification would increase the probability of arc faults in the wire system.Arc can ignite the combustibles by the arc column or hot droplets,which has high fire risks.Arc faults have triggered several catastrophic aeronautical accidents in the past.Electrical fire safety is a top priority of aircraft in the future.An in-depth understanding of the arc fault ignition mechanism plays a crucial role in preventing arc fires and optimizing wire layout.This review article performs a comprehensive summary of relevant research concerning the fire risks of arc faults,the causes of arc faults in the wire system,and the ignition behaviors of arc faults.The main findings regarding the direct ignition of arc faults and ignition of hot droplets are emphasized.The arc ignition characteristics in existing research are firstly summarized,including the arc ignition experiment platforms and thermal hazard characteristics of arc faults.Additionally,the generation,impacting process,and ignition characteristics of hot droplets are then presented.Finally,the limitations in existing research about ignition characteristics of arc faults are also outlined,while identifying the future research needs of fires caused by arc faults.

A wavelet packet based method for adaptive single-pole auto-reclosing

We present a new algorithm for adaptive single-pole auto-reclosing of power transmission lines using wavelet packet transform. The db8 wavelet packet decomposes the faulted phase voltage waveform to obtain the coefficients of the nodes 257, 259 to 262. An index is then defined from the sum of the energy coefficients of these nodes. By evaluating the index, transient and permanent faults, as well as the secondary arc extinction instant, can be identified. The significant advantage of the proposed algorithm is that it does not need a threshold level and therefore its performance is independent of fault location, line parameters, and operating conditions. Moreover, it can be used in transmission lines with reactor compensation. The proposed method has been successfully tested under a variety of fault conditions on a 400 kV overhead line of the Iranian National Grid using the Electro-Magnetic Transient Program (EMTP). The test results validated the algorithm’s ability in distinguishing between transient arcing and permanent faults and determining the instant of secondary arc extinction.