Circuit Breaker Operation Research Articles

Analysis of Interruption Performance of DC Vacuum Circuit Breaker Under Field and Circuitry Coupling in Electromechanical System

Analysis of Interruption Performance of DC Vacuum Circuit Breaker Under Field and Circuitry Coupling in Electromechanical System

Initial Characteristics of Submillimeter Metal Particles in GIS under Impact Vibration

As a critical component within power systems, Gas Insulated Switchgear (GIS) is notably susceptible to insulation degradation due to submillimeter metal particles, compromising its operational safety and stability. Moreover, impact vibrations induced by circuit breaker operations can dislodge particles that typically adhere to the interior walls, causing them to become airborne and thereby intensifying their movement and discharge activities. To investigate this phenomenon, this study establishes a testing platform where alternating current (AC) voltage is superimposed with impact vibration. A camera system, interfaced with an upper computer, is used to capture the real-time motion behavior of the particles. This study focuses on characterizing the initial movement of submillimeter metal particles of varying sizes under the influence of impact vibration by analyzing critical voltages, such as the initial lift-off voltage, stable jumping voltage, and extinction voltage. Furthermore, the effects of introducing large, centimeter-scale spherical metal and rubber particles on these initial characteristics are examined. The findings provide crucial insights into the initial behavior of submillimeter metal particles in GIS, particularly in relation to circuit breaker operations.

Study on the vacuum arc characteristics between novel straight slot transverse magnetic contacts with auxiliary slots on the back

The motion stability of the vacuum arc between TMF contacts significantly affects the breaking capacity of vacuum switches. The vacuum arc movement can be effectively controlled by slots on the TMF contacts to provide the necessary driving force. However, the necessary cross-slot movement of the arc affects its stability. In this paper, a novel straight-slot transverse magnetic field (SSTMF) contact structure with additional auxiliary slots on the back is proposed to improve current distribution and avoid stagnation at the contact center. The simulation analysis was conducted on the force acting on the arc at different positions and the magnetic field distribution between the contacts. Additionally, the arcing experiments were performed in a demountable vacuum chamber for both novel and traditional SSTMF contacts. The SEM analyses were carried out for the contacts after the experiments. Combined with simulation and comparative experimental results, it is verified that the auxiliary slots can improve the control and driving effect on the arc. This can provide ideas and references for future contact design and improve the breaking performance of vacuum circuit breakers.

Beyond seen faults: Zero-shot diagnosis of power circuit breakers using symptom description transfer

Power circuit breakers (CBs) are vital for the control and protection of power systems, yet diagnosing their faults accurately remains a challenge due to the diversity of fault types and the complexity of their structures. Traditional data-driven methods, although effective, require extensive labeled data for each fault class, limiting their applicability in real-world scenarios where many faults are unseen. This paper addresses these limitations by introducing symptom description transfer-based zero-shot fault diagnosis (SDT-ZSFD), a method that leverages zero-shot learning for fault diagnosis. Our approach constructs a fault symptom description (FSD) framework, which embeds a fault symptom layer between the feature layer and the label layer to facilitate knowledge transfer from seen to unseen fault classes. The method utilizes current and acceleration signals collected during CB operation to extract features. By applying sparse principal component analysis to these signals, we derive high-quality features that are mapped to the FSD framework, enabling effective zero-shot learning. Our method achieves a satisfactory recognition rate by accurately diagnosing unseen faults based on these symptoms. This approach not only overcomes the data scarcity problem but also holds potential for practical applications in power system maintenance. The SDT-ZSFD method offers a reliable solution for CB fault diagnosis and provides a foundation for future improvements in symptom-based zero-shot diagnostic mechanisms and algorithmic robustness.

PMSG-based wind farm high-voltage ride-through improvement for single-pole tripping of circuit breakers

For transient single phase-to-ground (SPG) faults in transmission lines, single-pole circuit breaker (SPCB) operation can improve system reliability. This issue is more critical in transmission lines emanating from wind farms (WFs). In the large-scale WFs, the grid codes necessitate that wind generation remains in operation during the transmission line faults. For this purpose, the grid codes focus on the development of fault-ride-through (FRT) requirements. In this paper, it is shown that after the SPCB operation, the terminal voltage of the permanent magnet synchronous generator (PMSG)-based wind turbine (WT) rapidly increases and may cross the high-voltage ride-through (HVRT) boundary. Therefore, the WT terminal overvoltage after the SPCB operation may result in undesirable tripping of the WT. The obtained results in this paper show that in most cases both the coupled and decoupled sequence controllers of the WT converter equipped with the FRT requirements are not able to improve the HVRT performance after the SPCB operation. To enhance the HVRT performance of PMSG-based wind turbines after the SPCB operation, a dc-link chopper controller is proposed. EMTP-RV simulation results on the IEEE 118-bus and 5-bus systems show the success and effectiveness of the proposed method.

A new fault detection and relay coordination technique for low voltage DC microgrid

Integration of various distributed generation units in the DC distribution network creates an outsized impact on magnitude and direction of fault current. The specific behaviour of fault current during a short circuit fault demands quick and reliable detection and isolation of fault, which poses a significant challenge in developing an effective protection and coordination scheme for DC microgrids. In this regard, a new fault detection and relay coordination algorithm is proposed for a Low voltage DC (LVDC) microgrid, which utilizes inverse time relay characteristics based on variance of fault current. While the relay responds and picks up during both internal and external faults, its operation is automatically limited upon operation of the downstream circuit breaker without the need for any communication channel. The efficacy of the proposed strategy is evaluated by modelling a mesh-connected DC microgrid network using PSCAD/EMTDC software. The protection coordination problem is developed as a constraint non-linear optimization problem to determine optimal relay settings. The proposed approach has been tested by simulating various types of faults at different fault locations and fault resistances along with various microgrid operating modes. The results suggest that the proposed strategy stands out by optimizing relay operating time and providing backup protection while upholding relay coordination. A comparative assessment of the proposed technique with existing ones proves its effectiveness in terms of swift relay tripping time, better immunity against noise, and independency against microgrid operating mode and topology.

Power system fault diagnosis with quantum computing and efficient gate decomposition

Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers. However, most classical methods suffer from significant time-consuming, memory overhead, and computational complexity issues as the scale of the power system concerned increases. With rapid development of quantum computing technology, the combinatorial optimization method based on quantum computing has shown certain advantages in computational time over existing methods. Given this background, this paper proposes a quantum computing based power system fault diagnosis method with the quantum approximate optimization algorithm. The proposed method reformulates the fault diagnosis problem as a Hamiltonian by using Ising model, which completely preserves the coupling relationship between faulty components and various operations of protective relays and circuit breakers. Additionally, to enhance problem-solving efficiency under current equipment limitations, the symmetric equivalent decomposition method of multi-z-rotation gate is utilized. Furthermore, the small probability characteristics of power system events is utilized to reduce the number of qubits. Simulation results based on the test system show that the proposed methods can achieve the same optimal results with a faster speed compared with the classical higher-order solver provided by D-Wave.

Mitigation of overvoltage in LVDC distribution system with constant power load using generic energy storage system

The operation of a high-speed DC circuit breaker can cause overvoltage transients in the Low Voltage Direct Current (LVDC) distribution system, especially when driving a constant power load (CPL). Without adequate damping, the destabilizing effect of the CPL can push the system towards instability. This paper proposes a novel approach to mitigate over-voltage transients caused by DC circuit breaker operation in the LVDC system using a generic energy storage system (GESS). The paper begins by introducing the concept, modeling, coordinated operation and practical application of GESS. GESS employs both power-centric storage, such as supercapacitors, to limit the switching over-voltage within safe limits, and energy-centric storage, such as batteries, to ensure the energy sustainability. A state-space model of a detailed LVDC distribution system with CPL and GESS is subsequently developed. Additionally, to ensure system stability, analytical expressions are derived to determine the required sizing of the power-centric storage under different case scenarios. Simulation analysis using MATLAB's Control System Toolbox validates that GESS can stabilize voltage transients and reduce overshoots within 10 ms. Moreover, the proposed GESS solution is proven to be more reliable and cost-effective than supercapacitor and hybrid energy storage solutions. It is also scalable to larger LVDC networks and adaptable to different load scenarios.

Smart Safety with Password Based GSM Module Controlling Circuit Breaker

Abstract: This paper focus on Smart safety with password based GSM module controlling circuit breaker. In our daily life, Safety is the major concern for all activities. Accidental death of a lineman is often read and proven in current scenario. In view, safety measures to protect operators are considered to be very necessary in current working. Using passwords for security, Electrical lineman security systems are used to control circuit breakers. Serious electrical accidents occurs becoming increasingly, when repairing power lines. It is happen due to lack of communication and coordination between maintenance and substation personnel. In the proposed system, the on and off line turning operation with the lineman to ensure the safety of linemen. For that, a secure password is required to operate the breaker operation and maintenance point of view. First request is registered and password is sent to the line operator's mobile phone and GSM module by AVR microcontroller. Entered password and password received by the GSM receiver are compare. If password is match, the operation of circuit breaker will be smoothly operate. The operator gave three chances for incorrect password otherwise message will appear on the LCD display for security purposed. It also sent the message control room regarding unauthorized access to the system.

Development and Application of PIKH-Type Current Sensors to Prevent Improper Opening of Parallelly Connected DC Vacuum Circuit Breakers

This article describes the development of current sensors used in DCU-type high-speed circuit breakers. DCU-type circuit breakers use the principle of turning off a constant short-circuit current by means of countercurrent. The article presents a new current sensor design called PIKh, which uses Hall sensors to measure current and determine its direction. PIKh sensors allow parallel operation of high-speed circuit breakers during the “parking” operation. The article includes the algorithm and principle of operation of the PIKh sensor. The proposed solution was verified on an electric traction vehicle.

Investigation of Partial Discharge Characteristics inside Vacuum Interrupter with Various Floating Shield Potentials

The reliable operation of vacuum circuit breakers (VCBs) plays an important role in the power system's reliability. The common cases which lead to the failure in the VCB are related to the loss of vacuum inside the vacuum interrupters (VIs). VIs commonly loses the vacuum with a higher leakage rate, resulting in a decrease in discharge voltage and partial discharge (PD) inside the VI which can lead to the eventual failure of the VCBs. Detecting vacuum leakage at the early stage became an important issue. In the prior study, vacuum failure was studied by detecting PD characteristics inside the VIs by regulating the different internal pressures. This study introduces a novel approach to investigating vacuum leakage within the VIs by detecting PD characteristics under various floating shield potentials to study the possibility of shield potential control on PD measurement. Comparing the experimental results measured at different internal pressures under various shield potentials, this study highlights the measurement of PD characteristics and the possibility of shield potential control on PD measurement. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Novel second zone acceleration technique for distance relay utilizing sequence voltages

An algorithm for second zone acceleration of the distance relay utilising the sequence voltages along with healthy phases impedances is presented in this paper. Specifically, the algorithm employs variation in sequence voltage ratio indices to sense the single-pole remote circuit breaker operation (RCBO), while utilising both magnitude and angle of the healthy phase impedance for sensing three-pole RCBO operation. Additionally, the developed algorithm can also identify the faulty phases based on variations in impedance magnitude. To avoid false-trip during transient faults, impedance of the faulted phase before RCBO is compared with its value after RCBO. Performance of the proposed approach is validated for various internal and external faults covering addition of parallel link, presence of noise, different load angle, fault location, fault inception angle, fault impedance, source impedance and errors in measurement/transmission line parameters on an existing 230 kV transmission line modelled in PSCAD/EMTDC software. The results, obtained from both simulation as well as Hardware in Loop (HIL) simulation through laboratory prototype, designate that the proposed approach performs appropriately regardless of power flow direction, fault resistance magnitude, and light load conditions. The results also reveal that the suggested approach is able to accelerate trip within a cycle after RCBO event, which is comparable to or faster than many existing methods. Compared to several existing approaches in the literature, it also outperforms in terms of sensitivity, reliability and selectivity.

A novel accelerated trip scheme for AC grids based on open-switching traveling waves

The delayed operation of a zone-2 impedance relay for handling faults on the end-section of a protected line can exacerbate power system instability. To accelerate the trip of a zone-2 circuit breaker (CB), many accelerated trip (AT) schemes have been proposed for AC power grids. However, these schemes remain by their pre-fault operating conditions, tripping modes, fault resistance, and fault types. Considering these limitations, this paper presents a novel AT scheme based on open-switching traveling waves (TWs) generated by CB operation. First, characteristic differences in the oscillation period and wavefront polarity of the open-switching TWs generated by remote CB operation under internal, remote busbar, and external faults are analyzed. Then, an identification criterion for open-switching TWs utilizing the order and number of wavefront polarities is proposed, thereby forming a new AT scheme. Finally, based on the PSCAD/EMTDC software, the effectiveness, sensitivity, and reliability of the proposed AT scheme are verified. The proposed AT scheme can operate at high speed without being affected by pre-fault operating conditions, tripping modes, or fault types, and its ability to endure fault resistance reaches 300 Ω.

Comparison of machine learning algorithms based on machine learning for the prediction of thermal plasma physical parameters of C4F7N and CO2 environmentally friendly gas mixtures

With the goal of “carbon peak and carbon neutrality,” the need for environmentally friendly gases to replace SF6, a high greenhouse effect gas, is urgent. C4F7N, as an environmentally friendly gas with the greatest potential to replace SF6 as an arc extinguishing medium in circuit breakers, can be mixed with CO2 to greatly improve the shortcomings of its high liquefaction temperature, and the calculation of the physical parameters of the mixed gas plasma is a prerequisite for the computational simulation of the arc process in the opening of circuit breakers. Because solving the physical parameters is expensive, based on the system of differential equations, this paper adopts several machine learning algorithms by mining the relationship between the data using the known physical parameter data to predict the results of the physical parameters to be solved under certain conditions, which greatly reduces the cost of computation. The machine learning algorithms used in this paper are K-nearest-neighbor regression, decision tree, random forest, support vector machine, and gradient boosting regression, of which for the support vector machine, hyperparameters find it difficult to determine the problem of optimization using the gray wolf algorithm. The prediction results of several algorithms show that they are more accurate and that the problem can be solved better by using the method of machine learning. Finally, the comparison results show that the support vector machine exhibits better performance in most cases and that the gray wolf algorithm can make the results of the support vector machine more accurate.

Adsorption and sensing SF6 decomposed gases (SO2, SO2F2, SOF2, H2S, and HF) on Ti and Co decorated B4CN3 monolayer- A DFT study

With frequent switching of high power and high voltage circuits, SF6 gas decomposes into low fluorine gases, which causes deterioration of SF6 gas. Therefore, such decomposed gases must be sensed and captured timely for the smooth operation of the SF6 power circuit breaker (PCB). The current study aimed to employ density functional theory (DFT) calculations to explore the adsorption and gas sensing properties of SF6 decomposed products (SO2, SO2F2, SOF2, H2S and HF) on titanium (Ti) and cobalt (Co) decorated B4CN3 monolayer. The findings revealed that pure B4CN3 could not capture gas molecules with sufficient adsorption energy and faced instantaneous release. Similarly, Ti and Co decoration can significantly activate the B4CN3 for adsorption and gas sensing. Adsorption analysis showed that SO2, SO2F2, SOF2, H2S, and HF chemically adsorbed on Ti decorated B4CN3 monolayer having adsorption energy of −1.31, −1.61, −1.35, −1.20, and −1.01 eV. Whereas, gas adsorption on Co decorated B4CN3 has −1.29, −1.58, −1.31, −1.18, and −0.95 eV, respectively. The gas sensing mechanism was evaluated by calculating band structure, work functions, and transport transmission. Despite having comparatively lower adsorption energies, Co decorated B4CN3 was found to be more sensitive to all gas molecules than Ti decorated B4CN3. The release time of gas molecules at room temperature can be shortened to nanoseconds either by rising temperature to 498 K or by just UV exposure at 298 K. Our study provides some significant theoretical insights into the gas sensing abilities of Ti and Co decorated B4CN3 monolayer for sensing SF6 decomposed products.

Efficient Methods to Reduce Arc Effects in Circuit Breakers

Abstract: This paper investigates the opening and non-opening processes of low voltage circuit breakers, the arc effects during short-circuit currents, and seeks to identify practical solutions to minimize potential damage. The reliable operation and protective capabilities of circuit breakers are crucial in power systems, especially during adverse conditions. Arc currents are a significant component of short-circuit scenarios in power systems. Additionally, arc currents typically occur between contacts during the opening of circuit breakers under normal conditions. Therefore, the components of circuit breakers play a vital role in mitigating the current flowing through the system. To diminish the destructive effects of electric arcs on circuit breaker parts, maintaining constant current values in the system is necessary, alongside conducting requisite tests and data collection. Understanding the properties and impacts of the components within the circuit breaker is also beneficial.

Enhancing Automation with Label Defect Detection and Content Parsing Algorithms

The stable operation of power transmission and distribution is closely related to the overall performance and construction quality of circuit breakers. Focusing on circuit breakers as the research subject, we propose a machine vision method for automated defect detection, which can be applied in intelligent robots to improve detection efficiency, reduce costs, and address the issues related to performance and assembly quality. Based on the LeNet-5 convolutional neural network, a method for the detection of character defects on labels is proposed. This method is then combined with squeezing and excitation networks to achieve more precise classification with a feature graph mechanism. The experimental results show the accuracy of the LeNet-CB model can reach up to 99.75%, while the average time for single character detection is 17.9 milliseconds. Although the LeNet-SE model demonstrates certain limitations in handling some easily confused characters, it maintains an average accuracy of 98.95%. Through further optimization, a label content detection method based on the LSTM framework is constructed, with an average accuracy of 99.57%, and an average detection time of 84 milliseconds. Overall, the system meets the detection accuracy requirements and delivers a rapid response. making the results of this research a meaningful contribution to the practical foundation for ongoing improvements in robot intelligence and machine vision.

The Influence of Mechanical Deformation Consideration on the Results of the Calculation of the Vacuum Circuit Breaker Drive Shaft

One of the important directions of theoretical, computational and experimental research related to the improvement and development of new design elements of modern electrical devices, primarily medium voltage circuit breakers and contactors, is the study of not only electromagnetic, but also mechanical processes in these electrical devices. The paper is devoted to the creation and use of computational models for calculating mechanical forces and deformations of an absolutely rigid and real drive shaft of a medium voltage vacuum circuit breaker in static mode with the aim of quantitative comparison of the obtained numerical results. Calculation studies are performed using the finite element method. A comparative analysis of the calculation of mechanical stresses in the drive shaft of a vacuum circuit breaker in a static mode for an absolutely rigid and real shafts is carried out in this paper on the basis of the developed models. The obtained results of computer modeling are given in detail in tabular and graphic forms, including the shape of the deflection of the medium voltage vacuum circuit breaker shaft at the maximum stroke of the actuator of the electrical device under study. It has been demonstrated that the mechanical deformation of the shaft causes a decrease in contact drop and contact pressure forces, but with a correctly selected cross-section, these values are not critical and have little effect on the circuit breaker operation (about 20% and 7%, respectively). It is shown that as a result of shaft bending, additional axial forces appear in the supports, which significantly affect the choice of bearings according to the equivalent static load.

Influence of Ultra-High-Voltage hybrid reactive power compensation on interruption performance of circuit breakers under different faults

For extremely large ultra-high-voltage (UHV) power transmission and distribution lines with typical project using hybrid reactive power compensation (HRPC), single-phase earth fault (1LG), three-phase ground fault (3LG), phase-to-phase fault (2LS), and two-phase grounding fault (2LG) often occurs. Circuit breaker is one of the most critical equipment of UHV transmission system. And the interruption performance is crucial to circuit breakers’ breaking capability. In this study, formal expressions of the indicators for the interruption performance of the circuit breaker are deduced in case of different faults based on the equivalent-valued parameter circuit based on the structure a UHV demonstration project. The simulations are used to validate the accuracy of formal expressions. Then, the influence of such factors as the location of the fault and the degree of HRPC on the interruption performance of the 1LG, 2LG, 3LG, and 2LS is analyzed. Finally, the interruption performance of circuit breakers under different faults are compared. A quantitative evaluation of the influence of changes in the relevant indicators on the interruption performance of circuit breakers can provide a technical basis for choosing the appropriate design of the circuit breaker in light of the application as well as equipment development and assessment.© 2017 Elsevier Inc. All rights reserved.

Research on Circuit Breaker Operating Mechanism Fault Diagnosis Method Combining Global-Local Feature Extraction and KELM.

In response to the lack of generality in feature extraction using modal decomposition methods and the susceptibility of diagnostic performance to parameter selection in traditional mechanical fault diagnosis of high-voltage circuit breaker operating mechanisms, this paper proposes a Global-Local feature extraction method based on Generalized S-Transform (S-Translate) combined with Gray Level Co-Occurrence Matrix (GLCM) and complemented by Maximum Relevance and Minimum Redundancy (mRMR) feature selection. The GL (Global-Local)-mRMR-KELM fault diagnosis model is proposed, which employs the Kernel Extreme Learning Machine (KELM). In this model, the original time-frequency domain features and the time-frequency features of the Generalized S-Transform matrix of vibration signals under different states of the circuit breaker are first extracted as global features. Then, the GLCM is obtained to extract texture features as local features. Finally, the mRMR and KELM are comprehensively applied to perform feature selection and classification on the dataset, thereby accomplishing the fault diagnosis of the circuit breaker's operating mechanism. In this study, the 72.5 kV SF6 circuit breaker operating mechanism is taken as the research object, and three types of mechanical faults are simulated to obtain a vibration signal. Experimental results verify the effectiveness of the proposed GL-mRMR-KELM model, achieving a diagnostic accuracy of 96%. This research provides a feasible approach for the fault diagnosis of circuit breaker operating mechanisms.