High-voltage Circuit Research Articles

Reconfigurable Large-Current and High-Voltage Test Bench for HVDC Circuit Breaker Verification

This article presents a novel circuit configuration of a high-voltage direct current circuit breaker (HVdcCB) test bench that is based on a modified H-bridge modular multilevel cascaded converter (MMCC). The modified MMCC is composed of fewer H-bridge cells, and it can be reconfigured during operation to allow the proposed test bench to output large current or high voltage for the current breaking and dielectric withstand tests. Although simultaneous output of large current and high voltage is not possible, the maximum transient interrupt voltage (TIV) withstand test can be performed with reduced ratings. The controllable output allows generation of complex waveforms to simulate a wide range of fault conditions. Furthermore, the modified MMCC has some inherent safety features that can reduce the need for additional protective equipment in case of operational failure of the HVdcCB. In contrast, the conventional charged capacitor and inductor-based designs cannot generate arbitrary waveforms, are only suitable for current breaking tests, and require additional circuits to generate initial conditions for the HVdcCB. AC short-circuit generator-based designs offer one degree of freedom for control of the output waveforms and can sustain the maximum TIV withstand test. However, the ac output is unsuitable for the dielectric withstand test, and additional circuits are required to provide initial conditions for the HVdcCB. The proposed test bench circuit configuration is verified using a downscaled experimental test bench that consists of a total of nine H-bridge cells with an equivalent switching frequency of 92.5 kHz.

Investigations on Wide-Gap Al0.21Ga0.79N Channel MOS-HFETs With In0.12Al0.76Ga0.12N Barrier/Buffer and Drain Field-Plate

This work investigates, for the first time, wide-gap Al0.21Ga0.79N channel metal-oxide-semiconductor heterostructure field-effect transistors (MOS-HFETs) with In0.12Al0.76Ga0.12N barrier/buffer and drain field-plate (DFP) designs. High-k and wide-gap Al2O3 was grown as the gate oxide and surface passivation by using non-vacuum ultrasonic spray pyrolysis deposition (USPD) technique. A control device having the same epitaxial layers, except with In0.12Al0.88N barrier/buffer was studied in comparison. Enhanced spontaneous polarization effect, improved interfacial quality, and enhanced carrier confinement have been achieved by using the In0.12Al0.76Ga0.12N barrier/buffer design, which has successfully resulted in improved carrier transport, increased electron concentration, and high current densities. The present In0.12Al0.76Ga0.12N/AlN/Al0.21Ga0.79N MOS-HFET design with (without) DFP design has demonstrated superior maximum drain-source current density (IDS, max) of >1 (>1) A/mm at VDS = 20 V, high saturated drain-source current density at VGS = 0 V (IDSS0) of 791.1 (755) mA/mm, and low specific on-resistance (Ron, sp) of 2.83 (2.81) mΩ/cm2. High device figure-of-merit (FOM) on BVDS2/Ron, sp of 93.7 (75.4) MW/cm2 was also obtained with the three-terminal on-state drain-source breakdown voltage (BVDS) of 515 (460) V. The present design is promisingly advantageous to high-current and high-voltage power-switching circuit applications.

A Novel Hybrid Transfer Learning Approach for Small-Sample High-Voltage Circuit Breaker Fault Diagnosis On-site

Although the data-driven fault diagnosis method has achieved perfect diagnosis of high-voltage circuit breakers (HVCBs) mechanical fault under the massive data built in the laboratory, it is still a challenge to train a high-precision and robust diagnosis model under the condition of small samples on-site at this stage. To solve the above issues, this paper proposes a novel hybrid transfer learning to realize small-sample HVCB fault diagnosis on-site. To fully learn domain discriminative features and domain matching, this paper simultaneously introduces domain adaptation transfer learning and domain adversarial training into small-sample HVCB diagnosis on-site. At the same time, the two kinds of feature transfer learning are combined through ensemble learning to get the final diagnosis result. To extract discriminative features that characterize HVCB faults, this paper constructs a one-dimensional attention residual convolutional neural network, which can ensure that the network pays attention to key features while fully extracting temporal fine-grained information. The experimental results show that the hybrid transfer learning proposed in this paper achieves 94.69% accuracy of small-sample HVCB fault diagnosis on-site, which is significantly higher than other methods. It has laid a solid foundation for small-sample HVCB fault diagnosis on-site.

Few-Shot Mechanical Fault Diagnosis for a High-Voltage Circuit Breaker via a Transformer–Convolutional Neural Network and Metric Meta-Learning

Few-Shot Mechanical Fault Diagnosis for a High-Voltage Circuit Breaker via a Transformer–Convolutional Neural Network and Metric Meta-Learning

DIGITAL APPROACH TO THERMIONIC EMISSION CURRENT TO VOLTAGE CONVERSION FOR HIGH-VOLTAGE SOURCES OF ELECTRONS

The thermionic emission current is used in many vacuum devices such as evaporators, rare gas excimers, or electron beam objects for high-energy physics. The stability of the thermionic emission current is a very important requirement for the accuracy of those devices. Hence, there is a number of control systems that use a feedback signal directly proportional to the emission current in order to stabilize the thermionic emission current. Most of them use feedback from a high-voltage anode circuit to a low-voltage cathode circuit. However, there is a novel solution that uses linear cathode current distribution and processing of two cathode circuit voltage signals for converting the emission current to voltage. However, it is based on old-fashioned analog technology. This paper shows the thermionic emission current to voltage conversion method with the use of a digital control system. A digital realization of a multiplicative-additive algorithm is presented and proper work in closed-loop mode is confirmed.

Fault identification of high voltage circuit breaker trip mechanism based on PSR and SVM

AbstractThe trip mechanism is a weakness in circuit breakers. Traditional fault identification based on the coil current is difficult to report early mechanical defects such as coil‐plunger jam. Here, the vibration signal during the trip process was extracted. Based on the coil current signal and vibration signal, the characteristics of the trip mechanism are analyzed. The phase space reconstruction (PSR) method is used to extract features from the vibration signal. Combined with the features from the coil current waveform, the feature set representing the health condition of the trip mechanism is proposed. The fault simulation tests are carried out and the variation of current vibration characteristics under fault conditions is studied. The fault identification model based on a support vector machine (SVM) is proposed and compared with the identification results when features are extracted from a single signal. When the power supply voltage is dispersed, the prediction accuracy of fault identification is 83.3% considering only the features of the current waveform or vibration signal. And the identification accuracy rises to 96.7% while using the feature set of current and vibration signals. On basis of the current signal, the method further combines the vibration signal so that the robustness of defect identification improves.

Fault diagnosis method of high voltage circuit breaker based on the combination of time-frequency multi-characteristics of acoustic signal

Aiming at the problem of accurately identifying the mechanical state of circuit breaker in the actual operation environment, a new fault diagnosis method of high voltage circuit breaker based on the combination of time-frequency multi-characteristics of acoustic signal was proposed. Firstly, the background noise database was established to remove the template noise. On this basis, the adaptive wavelet transform (AWT) was used to remove the residual noise. Then the kurtosis, crest factor and skewness indexes were extracted respectively to construct the time-domain characteristics. The acoustic signal was decomposed by variational mode decomposition (VMD) to obtain the IMF component. The power spectrum of the IMF was converted to the polar coordinates of the divided sub-region. The sensitivity of the main peak region was improved by the divergence factor, and the spectral difference entropy characteristics were calculated. The two jointly constructed the time-frequency multi-characteristics. Finally, kernel fuzzy c means (KFCM) clustering was used to pre-classify the characteristics, and then support vector machine (SVM) was used to establish training models to realize mechanical state identification. The diagnosis result shows that the accuracy of time-frequency multi-characteristics combined with KFCM-SVM diagnosis method is 98.75 %. It can reflect the status information of circuit breaker from multiple dimensions, and has high practical popularization value.

A High-Efficiency Protection Circuit Integrating Semi-Soft Switching and Voltage Limiting Functions for Solid-State Switch Applications

Despite the high performance of high-voltage direct current circuit breaker (CB) technology, its high cost restricts its further development. Thus, this article proposes a high-efficiency protection circuit for solid-state switches (SSs) that integrates semisoft switching and voltage limiting functions. The protection circuit also does not resonate with the system inductance which in turn does not affect the reclosing operation of the CB. The novel SS scheme reduces the cost and simplifies the layout of the SS. The special constraints for the parameter design of power electronics, gaps, and metal oxide varistors (MOVs) are proposed in this article for the first time, and a parameters design method that solves the transient power shock and voltage spike problems during the large current breaking process under multiple constraints is formed. Finally, an SS prototype is developed to verify the feasibility and the strong surge and turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> ability of the novel SS and to test the robustness of the series-connected gapped-MOV circuits.

Digital twin-oriented multi-physics field simulation analysis of high-voltage SF6 circuit breakers

Circuit breakers are important components for removing short circuits in power systems and ensuring safe operation. The operation of circuit breakers may not be predicted and thus cause accidents, so there is an urgent need to innovate means to assess the operation status of power equipment and monitor the operation status of power grids in full real time, to improve the monitoring capability of major key equipment, and to study key technologies for the digital twin of circuit breakers to support the safe and stable operation of transmission networks and the digital transformation of energy systems. This paper establishes the multi-physics field coupling calculation model of the circuit breaker opening process, completes the simulation calculation of the circuit breaker opening process, gets the distribution and change trend of parameters such as electric field, pressure, temperature, density, and airflow speed inside the interrupting chamber, and analyzes the flow characteristics inside the interrupting chamber in different opening processes. We select the characteristic parameters and provide data support for the establishment of fault diagnosis based on the digital twin of the circuit breaker.

Optimized fuzzy controller in precise circuits monitoring the current from resistance shunt in high-voltage DC circuits

Due to the low value of the resistance shunt, the measurement of low value current is a metrological problem. Properly selected processing constant and measurement system allows to minimize the metrological error. The proposed system consists of two identical non-inductive resistance shunts (125 µΩ) for measurement current. One of them is used to estimate the gain, the other is to measure the current. The amplification of the signal from the measuring shunt is controlled digitally by the fuzzy controller algorithm. The role of the intelligent system is to select the processing constant in order to use the dynamic range of the measuring system. The microprocessor parameters affect the efficiency of the intelligent algorithm. For this reason, part of the fuzzy controller should be implemented in the optimized form in order to relieve the microcontroller from calculations. The easiest way is to use operational amplifiers. Mention above the circuits act as a controller function block for fuzzification the output signal from the additional shunt. Takagi Sugeno Kang's inference system was selected in the proposed system due to the lack of a defuzzifier, which influences into its speed of operation. Carrying out computer simulations proved the effectiveness of the proposed system.

Application of High-voltage Circuit Breaker Status Evaluation Method Based on Primary and Secondary Integrated Switch Detection Platform

This paper proposes a high-voltage circuit breakers status evaluation method based on the primary and secondary integrated switch detection platform to cope with the poor effect of existing evaluation methods. A high-voltage circuit breaker status evaluation index system was determined in combination with the actual situation of high-voltage circuit breakers. The subjective weight of the status of the high-voltage circuit breaker was determined with the analytic hierarchy process, the objective weight of the status of the high-voltage circuit breaker was calculated by the entropy method, and the analog acquisition accuracy of the high-voltage circuit breaker was improved with the amplification circuit design of the genetic algorithm. After the weight was determined, the overall weighted evaluation was performed, and the status of the high-voltage circuit breaker was evaluated through primary and secondary integration. Through comparative experiments, it can be seen that the results of the weight proportion test on the high-voltage circuit breaker status evaluation based on the primary and secondary integration are greater than that of the traditional high-voltage circuit breaker status evaluation method. Therefore, the designed evaluation method based on the primary and secondary integration can be better applied to the distribution network and protect the circuit.

On Treatment of Some Physical Properties of Gas in Simulation of High-Voltage SF6 Circuit Breakers

Abstract Simulation of unsteady flow of SF6 gas in a simplified high-voltage circuit breaker model describing the nozzle, contacts and their nearest surrounding is presented. SF6 is considered as viscous, compressible, real gas described by Redlich-Kwong model. Heat transfer is taken into account due to the gas compressibility. The heat source, triggered by the electric arc between the contacts, was out of the scope of the current research, thus it was not included in the simulations presented. Turbulence, caused by the gas viscosity, is described using realizable k-ε model. In the simulation model, one of the contact sides – electrodes, is considered as moving at prescribed velocity. The part of the space ‘swept’ by the moving electrode is considered as the gas with imposed artificially increased viscosity in order to imitate the rigid body behaviour. Thus, no moving parts of the computational mesh are used in the model. The conservation equations of mass, momentum and energy, given in integral form, are solved using a finite-volume method on unstructured computational grids.

A fuzzy-logic-based method for maintenance prioritization of high-voltage SF6 circuit breakers, considering uneven wear

High-voltage circuit breakers are among the most critical elements of the switching nodes of the power system. The localization of failures and the restoration of the normal operational mode of the power system are largely determined by the reliable operation of circuit breakers when switching off short circuit currents. This paper presents a fuzzy logic-based method to estimate the reliability of high-voltage SF6 circuit breakers and to set priorities for the maintenance schedule. In this method a realistic mathematical model is combined with a fuzzy inference system, and its effectiveness was tested with a MATLAB-Simulink model. Based on the simulation results, a preventive maintenance strategy for high-voltage SF6 circuit breakers can be proposed for particular operational states and conditions.

Principal component analysis (PCA) based sparrow search algorithm (SSA) for optimal learning vector quantized (LVQ) neural network for mechanical fault diagnosis of high voltage circuit breakers

An essential piece of equipment for the protection and management of the electricity grid is a high voltage(HV) circuit breaker. The reliability and stability of the electricity grid are directly affected by the condition of operation of a high voltage circuit breaker. This study proposes a PCA-SSA-LVQ-based high-voltage circuit breaker diagnosis method to identify mechanical faults of high-voltage circuit breakers more quickly and effectively. Laboratory simulation of vibration signals for different fault states of high voltage circuit breakers. Finite intrinsic mode functions(IMF) are obtained by empirical modal decomposition(EMD) of the simulated vibration signal. The envelope spectrum of the IMF is extracted using the Hilbert envelope transform, and the concept of information entropy is used to determine the entropy value of the envelope as the characteristic quantity of the signal. Using principal component analysis, one can decrease the eigenvectors’ dimension. The high voltage circuit breaker LVQ neural network fault diagnosis model is made, and the initial weight of the LVQ neural network is optimized using the SSA optimization algorithm. The accuracy was improved in the end. The optimized and non-optimized LVQ neural networks were compared. The results show that the PCA-SSA-LVQ neural network has a higher diagnostic rate and faster training convergence. The main contribution of this paper is to reduce the redundancy of feature vectors using the PCA algorithm, optimize LVQ neural network by the SSA algorithm, and creatively use these three algorithms together. The training speed and the accuracy of state recognition are improved.

Study of Sulfur Hexafluoride-Nitrogen Mixtures Contaminated by Copper Vapors in High Voltage Circuit Breakers

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

SF6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents.

Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF6 gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an HVCB based on the vibrational signal. First, for a 40.5-kV SF6 HVCB prototype, a mechanical vibration detection system along with a high-current generator to provide the test current is designed. Given this, vibration test experiments are carried out, and the vibration signal data under various currents and corresponding contact states are obtained. Afterward, a feature extraction method based on the frequency is designed. The state of the HVCB contacts is then determined using optimized deep neural networks (DNNs) along with the method of adaptive moment estimation (Adam) on the obtained experimental data. Finally, the hyperparameters for the DNNs are tuned using the Bayesian optimization (BO) technique, and a global HVCB contact state recognition model at various currents is proposed. The obtained results clearly depict that the proposed recognition model can accurately identify five various contact states of HVCBs for the currents between 1000 A and 3500 A, and the recognition accuracy rate is above 96%. The designed experimental and theoretical analysis in our study will provide the references for future monitoring and diagnosis of faults in HVCBs.

Study on the performance of high-voltage deep ultraviolet light-emitting diodes.

This study fabricated high-voltage, low-current DUV-LEDs by connecting two devices. Due to better current spreading and the enhanced reflective mirror effect, high-voltage devices present a higher dynamic resistance, emission output power, wall-plug efficiency, external quantum efficiency, and view angle than single traditional devices. The study found that when the injection current was 320 mA, the maximum output power was exhibited at 47.1 mW in the HV sample. The maximum WPE and EQE of high-voltage DUV-LEDs were 2.46% and 5.48%, respectively. Noteworthily, the redshift wavelength shifted from 287.5 to 280.5 nm, less than the traditional device-from 278 to 282 nm. Further, due to the uniform emission patterns in high-voltage devices, the view angle presents 130 degrees at 100 mA input current. In this study, the high-voltage device showed more excellent properties than the traditional device. In particular, it presented a high potential application in high-voltage circuits, which can remove transformers to eliminate extra power consumption.

Application of Bioinspired Antennas in the Monitoring of High Voltage Circuit Breakers

This paper presents a technique for circuit breaker radiometric monitoring using broadband plana monopole antennas (PMA). Considering that this work represents the continuity of a previous research, the antenna has been miniaturized using a bioinspired geometry based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Acer Macrophyllum</i> leaf. The monitoring system consists in measuring the signal radiated by electric arcs in circuit breaker poles during its switching operations. By analyzing these signals, it is possible to evaluate, non-intrusively, the equipment electric and mechanical status, providing important information to maintenance crews regarding the need for interventions. By performing laboratory tests, it was confirmed that the developed bioinspired PMA has adequate gain values, radiation pattern and frequency range to circuit breaker monitoring applications. Moreover, field tests on a 230 kV SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> circuit breaker were carried out, from which the proposed technique applicability was confirmed. The proposed monitoring technique can be considered a continuous and non-invasive solution, since the antennas can be placed at a safe distance from the equipment under analysis, without compromising the insulation. In the substation, the technique has the potential to detect problems of electrical and mechanical nature, since important operational parameters can be detected, such as opening time and pole synchronicity.

Method of Evaluating Dielectric Interruption Capability of High-Voltage Circuit Breaker

Two performance indices using the local dielectric strength are proposed to measure interruption capabilities for breaker terminal fault duties in high-voltage circuit breakers. The dielectric strength at a part in the insulating gas volume between arcing contacts surrounded by an insulating nozzle was evaluated by comparing the applied electric field strength with the critical electric field strength calculated from the gas flow properties. The first index quantifies the effect of suppressing the discharge evolution, which is calculated by integrating the ratio of the critical electric field to the applied electric field in the space between the arcing contacts. The second index expresses the ease of initiating dielectric breakdown, which is calculated by integrating the inverse of the first index in the range of space including the surface of the insulating nozzle. To determine the criteria for the performance indices, gas flow simulations were conducted under experimental conditions with 10–100% of the rated interrupting current. The region excluding failure cases was considered to be the high-performance area.

A Novel High-Voltage Gain Circuit Topology for Commutation Torque Ripple Reduction

The electronic commutation and the low inductance nature of the brushless dc motor (BLDC) deteriorate the expected performance. The ripples in the current waveshape are primarily due to the commutation of the phases, which is carried to produce a synchronously rotating magnetic field. This commutation ripples lead to mechanical pulsation and noise on the rotor side. This article presents a novel strategy for reducing the commutation torque ripple. The proposed topology uses a hybrid Ćuk voltage gain dc–dc converter at the front end, which has high voltage gain and which reduces voltage ratings of the dc supply. An auxiliary switch is connected across the dc link of the inverter to control the rate of rising incoming phase current during the phase change of the inverter with the help of the dc–dc converter. A prototype of a 1HP BLDC motor is used to validate the proposed topology both analytically and experimentally.