High Voltage SF6 Circuit Breaker Research Articles

Algorithm for Automated Assessment of the Condition of a High-Voltage SF6 Circuit Breaker Based on a Limited Data Set

Algorithm for Automated Assessment of the Condition of a High-Voltage SF6 Circuit Breaker Based on a Limited Data Set

Simulation of auto-expansion high voltage SF6 circuit breaker breaking process considering valve motion

Simulation of auto-expansion high voltage SF6 circuit breaker breaking process considering valve motion

The Methodology for Evaluating the Operating State of SF6 HVCBs Based on IDDA.

To enhance the precision of evaluating the operational status of SF6 high-voltage circuit breakers (HVCBs) and devise judicious maintenance strategies, this study introduces an operational state assessment method for SF6 HVCBs grounded in the integrated data-driven analysis (IDDA) model. The relative degradation weight (RDW) is introduced as a metric for quantifying the relative significance of distinct indicators concerning the operational condition of SF6 HVCBs. A data-driven model, founded on critical factor stability (CFS), is formulated to convert environmental indicators into quantitative computations. Furthermore, an optimized fuzzy inference (OFI) system is devised to streamline the system architecture and enhance the processing speed of continuous indicators. Ultimately, the efficacy of the proposed model is substantiated through validation, and results from instance analyses underscore that the presented approach not only attains heightened accuracy in assessment compared to extant analytical methodologies but also furnishes a dependable foundation for prioritizing maintenance sequences across diverse components.

Graphene-Enhanced CuW Composites for High-Voltage Circuit Breaker Electrical Contacts

To address the issue of over-standard short-circuit currents in a power system, it is imperative to enhance the comprehensive performance of the electrical contacts, which serve as the lynchpin of circuit breakers, so as to improve the breaking capacity of high-voltage circuit breakers. Graphene, as the most prominent two-dimensional carbon material in recent years, has garnered widespread applications across various fields. In this study, graphene-enhanced CuW composites for high-voltage circuit breaker electrical contacts were prepared innovatively using integrated vacuum infiltration technology. The innovative graphene-enhanced CuW composites significantly improved the mechanical, electrical, and ablation resistance properties, and have been successfully applied in the 252 kV/63 kA high-voltage SF6 circuit breakers, achieving 20 times effective consecutive full-capacity short-circuit current breaking. It provides a new route for the development and application of high-performance CuW electrical contacts. Looking ahead, it is planned to extend their application to higher voltage grade high-voltage circuit breakers.

Analysis of Breakdown Phenomena of SF6-Gas Using Different Electrodes Configuration in High Voltage Application

This research investigates the breakdown voltage of SF6 gas using several electrode configurations, including Sphere-sphere, Rod-rod, Plate-plate, Sphere-plate, and Rod-plate, to guarantee sufficient clearance for an acceptable insulation level. The objective of the various electrode geometries is to produce a homogeneous and non-homogeneous electric field wherein the SF6 gas breakdown could be analyzed. The simulation under the influence of six gaps length be-tween electrodes (0.5cm, 1cm, 2cm, 3cm, 4cm, 5cm) were conducted. The lowest breakdown voltage is found in the Rod-rod electrode arrangement, followed by Plate-plate and Sphere-sphere electrode configuration. Compared with the Sphere-sphere electrode design, the Rod-rod electrode configuration is also asymmetric, with a substantially more inhomogeneous electric field. Based on the results, the Rod-plate and Sphere-plate arrangements appear to be asymmetrical. In the event of discharge and breakdown voltage, different electrode configurations have a significant influence. This study helps to identify the most suitable clearance and electrodes configuration in high voltage SF6 circuit breakers. A few researches were performed to find the breakdown voltage of SF6 gas in medium voltage applications under homogeneous electric stress. Some research paper also studied to find the breakdown voltage of SF6 gas under different temperature and pressure. However, this paper is based on finding out the breakdown voltage of SF6 gas in high voltage application providing homogeneous and non-homogeneous electric stress. This homogeneous and non-homogeneous electric field is designed using different electrodes configuration.

Application of DE-ELM Algorithm in SF6 Circuit Breaker Contact Ablation Evaluation

When assessing the ablation status of circuit breaker contacts, the average dynamic contact resistance of the arc contacts of high-voltage SF6 circuit breakers is crucial. The average dynamic contact resistance of arc contacts on circuit breakers under various current levels may be accurately predicted using a method based on a differential evolution algorithm and extreme learning machine (DE-ELM), which is suggested in this research. Combining optimization algorithms yields the ideal input weight and hidden layer bias of the ELM method. The DE-ELM approach has outstanding anticipation performance for anticipation data under various current levels when compared to other anticipation methods. Finally, an expert system for assessing the ablation state of contacts based on the DE-ELM algorithm is created using the average dynamic contact resistance data of arc contacts predicted by DE-ELM. As a guide for the upkeep of high-voltage SF6 circuit breakers, the ablation status of contacts is categorized into four grades: A-level ablation, B-level ablation, C-level ablation, and D-level ablation.

FUZZY MODELING OF SWITCHING EQUIPMENT FOR TASKS OF ASSESSING THE RISK OF EMERGENCY SITUATIONS IN THE EPS IN CASE OF ELECTRICAL EQUIPMENT FAILURES

Today in the electric power industry of Ukraine the issue of assessing the risk of EPS operation due to failures of electrical equipment is particularly important. Failures are associated with significant level of aging and low replacement rates of electrical equipment, also with the possible simultaneous emergency decommissioning of several elements as a result of terrorist attacks.
 Based on the analysis of the operating conditions of high-voltage switching equipment, standards and operational documentation method of diagnosing the technical condition of SF6 circuit breakers is proposed. This method is based on the use of fuzzy set theory.
 To assess the risk of power outages in the EPS in case of electrical equipment failures, a linguistic model is proposed for determining the total residual life and the probability of failure of SF6 high-voltage circuit breakers of various types. Which is based on the aggregation of information on the technical condition of individual functional units.
 An approach is proposed to take into account the importance of individual units of the circuit breaker in terms of the impact on the total residual life by weight coefficients determined due to failure statistics. The result of determining the total residual life is the ability to estimate the probability of failure on the observation time interval.
 Tuning and adaptation of the developed linguistic model of the SF6 circuit breaker to real operating conditions is provided by adjusting the parameters of the membership functions of the terms of the input linguistic variables using weighting coefficients and fuzzy inference with weighted average truth.
 The developed linguistic mathematical model for assessing the technical condition and probability of failure of SF6 circuit breakers can be used as a component of the complex of risk analysis programs in the EPS. And the formation of preventive actions to ensure the operational reliability of electrical equipment and regime reliability of the EPS in case of emergency equipment failures.

Analysis of SF6 contact based on QPSO-SVR

In the condition evaluation of the high-voltage SF6 circuit breaker, contact resistance and mass loss have a significant impact on the arc contact. To that end, this paper proposes a method based on quantum particle swarm optimization and support vector regression (QPSO-SVR), the implementation of which can effectively predict the contact resistance increment and mass loss of the circuit breaker arc contacts under different arc current conditions, and the best support vector regression (SVR) algorithm training parameters are obtained through experimental data. To validate the proposed method’s accuracy, it is compared to other prediction methods, and the results show that the QPSO-SVR method has good predictive ability for experimental data under different discharge parameters. The relative error of prediction for contact resistance increment is 3.023%, and the relative error of prediction for mass loss is 4.61%, indicating good accuracy and robustness. It can serve as a reference for the maintenance of high-voltage SF6 circuit breakers, which is useful. It is of great significance to the maintenance of SF6 circuit breaker.

An Online Non-Invasive Condition Assessment Method of Outdoor High-Voltage SF6 Circuit Breaker

Online monitoring of outdoor high voltage SF6 circuit breakers (HVCBs) is essential to detecting potential damages. To this end, the study of accurate and non-invasive monitoring methods has been significantly investigated in recent decades. Considering that HVCB vibration patterns carry important information about mechanical and electrical integrity and that vibration analysis requires a low level of invasiveness, this article presents methods of obtaining mechanism and reaction times using interference signals of outdoor high voltage SF6 circuit breakers (HVCBs). Compared to traditional methods of monitoring outdoor SF6 circuit breakers that are based on encoders, the proposed method presented ease of installation, as it only requires the insertion of accelerometers. The method of obtaining the mechanism time is based on the use of interference and auxiliary contact signals, in the time domain, where the accelerometer is installed, in the structure of the HVCB, makes it possible to guarantee the moment of the trip command. To obtain the reaction time of each HVCB pole, the envelope technique was applied with the Hilbert transform module of the hearing signal, filtered in a certain resonance band. The proof of the technique of analyzing the vibration of the signal in time was developed with laboratory tests of an HVCB, instrumented with accelerometers and angular encoders. The results obtained via vibration analysis were compared with those obtained via angular encoders and it was concluded that with the acceleration signals, in time, it is possible to obtain performance parameters of an HVCB from its displacement curve. Finally, the online monitoring of the circuit breaker applied in the field is presented, where the acquisition of trip current signals, the condition of the SF6 gas and extinguishing current signals were added to the instrumentation.

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.

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.

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.

An arc contacts life assessment method based on dynamic resistance measurement and bp neural network

Arc contacts ablation of high voltage SF6 circuit breaker will cause potential problems for safe operation of the grid. In view of the difficulty of predicting arc contacts life by existing methods, an arc contacts life assessment method based on dynamic contact resistance and BP neural network is proposed. The dynamic contact resistance-travel curve is obtained from the high-current ablation experiments, from which the data characterizing the arc contacts state is extracted as samples to train the neural model. The model is optimized by k-fold cross-validation method, which is finally validated by experimental results. The results show that the arc contacts life prediction value agrees well with the experimental value, which means that the BP neural network can effectively predict the arc contacts life and provide a basis for decision making for arc contacts overhaul and replacement.

Predominant reaction products and dielectric breakdown properties of gas mixtures consisting of SF6 and ablation products of C2F4/BN in the temperature range of 300–3000 K

For a high voltage SF6 circuit breaker equipped with a boron nitride (BN)-filled polytetrafluoroethylene ((C2F4)) nozzle, the predominant reaction products in a high-temperature SF6 mixture with vapor decomposition of C2F4 and BN at temperatures of 300–3000 K are determined based on calculations of equilibrium composition. The calculation is performed by considering the molecular products obtained by chemical reactions with boron atoms (e.g. BN, BS, BC, BF, BF2 and BF3), nitrogen atoms (e.g. N2, N3, CN, NS, NF, NF2 and NF3) and carbon atoms (e.g. CS, CS2, C2F4, CF2, CF3 and CF4). The results obtained for the C2F4–BN molar fraction of 20%–80% reveal that BF3, N2 and CF4, the molecules originating from the nozzle material, are produced at high molar fractions over a range of 300–3000 K. Such an evaluation of the gas composition allows the derivation of a reduced collision ionization coefficient α/N and a reduced electron attachment coefficient η/N of the gas, considering various electron impact processes such as BF3 + e BF2 + F− and CF4 + e CF3 + F−. The evaluation subsequently enables us to determine a critical reduced electric field strength causing . The results suggest that the decomposed C2F4–BN mixture at of 80% causes the reduction of to 110 Td in the range of 1000–2000 K at a gas pressure of 1.0 MPa. This strength is 20 Td lower than that determined separately for the SF6 gas mixture with only 80% C2F4 vapor decomposition, because of the CF4 molar fraction reduction in the SF6/C2F4–BN mixture.

Research on the wear and life of copper tungsten alloy contacts of high voltage SF6 circuit breakers

Three phase short circuit and two phase short circuit grounding fault of power system have a significant influence on the electrical life of circuit breaker contact. In this paper, the mathematical model of each component is established by Power System Analysis Software Package (PSASP), and the simulation model is built to simulate the dynamic state of the circuit breaker after different short-circuit faults. The simulated result confirms that contact electrical wear quantity related to the type of short circuit fault and the position of short circuit point. The size of short circuit current will directly impact electrical wear quantity and electrical life of circuit breaker contact.

State Evaluation of SF6 high Voltage Circuit Breaker based on improved Radar Chart and Catastrophe Progression Method

The comprehensive on-line assessment of power equipment health status was an important research content of power production and maintenance.According to the operation characteristics of SF6 high voltage circuit breaker, the hierarchical evaluation model of high voltage circuit breaker was established, and the subjective and objective weights were fitted and optimized by multiplication synthesizer; the improved radar chart method was applied to the importance evaluation of circuit breaker index; the final evaluation result of circuit breaker was obtained according to the catastrophe progression method, which made the evaluation process more intuitive and concise, and avoided the subjectivity. A practical example showed that the proposed model could objectively and effectively evaluate the state of high voltage circuit breaker.Compared with the traditional radar chart method, the improved radar chart method combined with the catastrophe series method solved the problems of information sharing and non-unique evaluation results among the indicators in the traditional radar chart method, which made the evaluation results more accurate and reasonable.

Research on data-driven method for circuit breaker condition assessment based on back propagation neural network

As the maintenance requirements are changed with the health status of equipment, in order to develop an optimal maintenance strategy, a data-driven nonlinear method is proposed to online assess the operating condition of circuit breakers. From the historical data resources with different timeliness, feature indicators are extracted based on the confidence improved by Bayesian probability. Then, an adaptive error back propagation (BP) neural network is improved to model the nonlinear correlation between the feature indicators and the operating conditions of the circuit breaker, by additional momentum factor, self-adaptive learning rate and improved momentum. Finally, combined with the inspection test and online monitoring data, the panoramic operating condition pf the equipment is objectively graded by the output model. Taking 500kV SF6 high-voltage circuit breaker as an example, combined with the data provided by China Yunnan Power Grid, the effectiveness of the proposed method is proved by sample tests and method comparison.

X-ray testing of high voltage oil-filled electrical equipment: Physical background and technical requirements

In this study the capability of X-ray technology to examine the internal elements of high-voltage equipment is reported for the first time. Samples of high-voltage minimum oil and SF6 circuit breakers were designed and tested to evaluate the X-ray images and compare with known artificial defects. The assessment of the influence of X-ray spectral energy characteristics on information obtained by X-ray imaging of objects having spread equivalent radiation thickness determined the technical requirements for this analysis.

Fault Analysis of High-Voltage Circuit Breakers Based on Coil Current and Contact Travel Waveforms Through Modified SVM Classifier

High-voltage circuit breakers (HVCBs) play a substantial protection role in power networks. The reliable operation of these critical components leads to an increment of resiliency and safety of power systems. It is essential to design a fault diagnostic system that detects the defects in preliminary levels and identify the origins to establish a precise maintenance task. This paper focuses on coil current and contact travel waveforms as significant signals that bear helpful information about the fault occurrence for a typical EDF, 72.5 kV, SF6 HVCB. Healthy and faulty signals simulated based on Michael Stanek's HVCB model in MATLAB, with performing some modifications in the actuating coil and operating mechanism. In the first step, to arrange an efficient fault recognition system, neural network and support vector machine (SVM) have been designed using the information of 475 simulated healthy and faulty HVCBs and verified for 200 new samples. In the second step, to improve the classification results, an additional distinction algorithm has been recommended for the cases in which two failure modes are detected by the classifier. Since any failure mode's impact on the selected features is different, the proposed diagnostic method makes a decision, between two classes of faults, based on the extracted pattern of each failure mode. The recommended method, which is a combination of commonly used classification techniques and the defined algorithm, leads to the more accurate diagnosis.

Artificial intelligence SF6 circuit breaker health assessment

This paper presents advance artificial intelligence (AI) methods for health assessment of high voltage SF6 circuit breakers. Paper presents an overview of monitoring and diagnostics of most important indicators of the state of high voltage SF6 circuit breakers. Special attention is devoted to identifying and determining indicator limit values which can be used by AI in order to create new health assessment. Fuzzy logic as a part of AI was applied to define fuzzy expert systems which will make decisions about the maintenance of circuit breakers. Three fuzzy expert systems are created to indicate the state of: contacts, the fluid for extinguishing the electric arc and the drive mechanism. Unsupervised machine learning (UML) was applied through the k-means cluster method and cluster tree for classifying and dividing the examined high-voltage circuit breakers into groups with similar state and probability of failure. Artificial neural network (ANN) as part of supervised machine learning (SML) is created in order to predict end-life and accelerated aging of tested circuit breakers. The presented AI methods can be used to improve health assessment of high-voltage SF6 circuit breakers.