Electric Power Equipment Research Articles

Enhanced DC surface discharge characteristics of epoxy composites treated by dielectric barrier discharge plasma fluorination and its mechanisms

Surface flashover is a destructive high-voltage discharge phenomenon greatly limiting the update of modern power electronic and electrical equipment. Surface plasma treatment is a high-energy, eco-friendly, and convenience method, it changes the surface properties and owns potential to improve flashover voltage. In the present work, plasma fluorination (PF) technique are used to treat EP/Al2O3 composites, surface morphology, element and bonds content, surface trap, conductivity, charging, and DC flashover voltage are tested and simulated, the effects of plasma on surface discharge are explained through the investigation from microscopic molecular reactions to macroscopic flashover characteristics. It indicates the 20 min PF modified sample exhibits the superior DC flashover performance, increasing by 17 % compare to untreated sample. During PF modification, the epoxy chains are degraded and fluorinated, the degradation rather than fluorination of molecular chains introduce large amounts of shallow traps into the composites, accelerating carriers’ migration and improving surface conductivity, causing surface charges to dissipate through surface conductance. Consequently, the surface electric field distortion degree reduces, and the subsequent gas ionization and plasma formation in the gas phase is suppressed, leading to the improvement of DC flashover voltage after PF modifications.

Target detection of helicopter electric power inspection based on the feature embedding convolution model.

This study aims to improve the helicopter electric power inspection process by using the feature embedding convolution (FEC) model to solve the problems of small scope and poor real-time inspection. First, simulation experiments and model analysis determine the keyframe and flight trajectory. Second, an improved FEC model is proposed, extracting features from aerial images in large ranges in real time and accurately identifying and classifying electric power inspection targets. In the simulation experiment, the accuracy of the model in electric power circuit and equipment detection is improved by 30% compared with the traditional algorithm, and the inspection range is expanded by 26%. In addition, this study further optimizes the model with reinforcement learning technology, conducts a comparative analysis of different flight environments and facilities, and reveals the diversity and complexity of inspection objectives. The performance of the optimized model in fault detection is increased by more than 36%. In conclusion, the proposed model improves the accuracy and scope of inspection, provides a more scientific strategy for electric power inspection, and ensures inspection efficiency.

Optimization of monitoring systems power cable lines

RELEVANCE. The length and complexity of the geography of medium voltage cable lines is at a high level. Such lines extend underground, on supports in the air. In order to constantly maintain the reliability of city power supply at a high level, any interruptions and accidents should be promptly corrected.TARGET. The main goal of the work is to develop the theory of medium voltage CL research, to practically and theoretically substantiate the search for the most convenient and effective installation for CL diagnostics, to study and develop possible modifications of CL diagnostic installations.METHODS. A variant of CL diagnostics based on the CPDA-60 installation is proposed, which makes it possible to find and localize the places where defects occur in the insulation based on the measurement and analysis of partial discharges (PD). Suitable for insulation monitoring in all types of high voltage cables. The CPDA installation can be used when testing new cable lines being put into operation, and to analyze the condition of old cables in operation.RESULTS. Cable lines require an integrated approach to diagnostics and monitoring, since the reliability of modern authentication systems for the generation and distribution of electricity is largely determined by the electrical reliability of electrical equipment. Technical diagnostics of equipment is a key link, the quality of which determines the efficiency of the processes of organizing production activities, strategic planning and renovation of electric grid assets.CONCLUSION. The study and analysis of the presented data and research allows us to form a conclusion regarding the method of measuring and localizing partial discharges (PD) in power cable lines (CL) using the Online Wire Testing System (OWTS) diagnostic system. The OWTS system allows real-time measurements without interrupting cable lines, making it especially valuable to the energy industry. Thanks to the introduction of advanced technologies and signal processing algorithms, the method has high accuracy and sensitivity to minimal manifestations of private discharges, which allows not only to detect, but also to accurately localize the location of defects in the insulation. The use of this method can significantly increase the service life of power cables, reduce the likelihood of sudden accidents and, as a result, reduce the cost of repair and maintenance of electrical power equipment. Ultimately, improvements in diagnostic and monitoring techniques, including the method of measuring and localizing PD in power lines using OWTS, represent a significant step towards improving the reliability and safety of electrical power systems. This will not only reduce operating costs, but also ensure uninterrupted and high-quality power supply to consumers.

Dielectric behavior and breakdown strength of glass fiber reinforced epoxy composites under dynamic mechanical fatigue

Glass fiber reinforced polymer (GFRP), used in insulating components like insulation rods, needs to withstand both high voltage and large dynamic mechanical fatigue during operation. In this paper, the effects of tension–compression fatigue loads on the dielectric properties of GFRP under various fatigue cycles and stress levels are investigated. The results show that DC conductivity has a strong negative correlation with stiffness, while breakdown strength is showing a positive correlation. Fatigue-induced internal damage could cause continuous charge accumulation and enhanced interfacial polarization, leading to the increase of dielectric constant by 46.89% and the reduction of breakdown strength by 15.05%, when the fatigue span ratio reaches 80% under 40% stress level. Understanding the evolution of dielectric properties of GFRP under dynamic mechanical fatigue conditions is helpful for ensuring the safe and stable operation of electrical power equipment subjected to both high voltage and fatigue loads.

Electrical breakdown mechanism and life prediction of thermal-aged epoxy/glass fibre composites

Epoxy/glass fibre composites possess excellent mechanical and electrical properties and are widely utilised in electrical and electronic power equipment. However, the composites exhibit relatively poor thermal conductivity, causing the temperature of the composites to increase during the operation of power equipment, resulting in a significant reduction in the electrical breakdown strength. Although the effects of thermal aging on polymeric materials have been widely studied, its influence on electrical strength mechanisms has not been investigated at the molecular level. In this study, epoxy/glass fibre composite specimens were subjected to accelerated thermal aging treatment for 360 h at 180 °C. Functional groups, molecular chain dynamics, and electrical breakdown are characterised using infrared spectroscopy, dielectric spectroscopy, and breakdown measurement. Subsequently, electrical breakdown mechanism and life prediction of the thermally aged composites are discussed. During thermal aging, the epoxy resin molecular chains undergo continuous oxidation and chain scission, which generate numerous polar functional groups and short chains and an increase in the free volume. This triggers an enhancement in the chain segmental dynamics, thereby significantly reducing the activation energy of the epoxy resin. After 360 h, activation energy decreased from 0.78 eV to 0.67 eV. The DC breakdown voltages of the specimens decreased from 168.28 kV/mm to 134.91 kV/mm. An insulation life prediction model for thermally aged epoxy/glass fibre composites is established based on the time-temperature equivalence theory. The prediction results indicate that the service life of the operational composites is approximately 11.2 years at 353 K, which is consistent with engineering experience.

Arc Plasma Analysis Technology to Accelerate the Development of Advanced Electric Power Equipment

Arc Plasma Analysis Technology to Accelerate the Development of Advanced Electric Power Equipment

Исследование существующих методов сушки увлажненной изоляции тяговых электродвигателей локомотива

Objective: consider the issue of increasing the reliability of electric locomotive traction motors, which depends on various factors. This article examines the factor of the impact of climate conditions on the operation of a locomotive. All attention is paid to the relevance of research into methods for drying the insulation of traction motors at the present time. It has been proven over many years of work that the most vulnerable part of the engine is insulation. All methods that are aimed at solving the assigned problems are listed. The article describes the principle of operation and technology of processes in each of these methods. From the proposed methods, efficiency indicators are derived from the perspective of technical and economic results, and some of their advantages and disadvantages are also noted. The article is based on a comparison of various methods that are aimed at solving current problems associated with increasing the reliability of traction rolling stock. Statistics on traction motor failures over the past three years are presented, and the reasons for moisture in the insulation of electric locomotive power equipment are described. The main methods and methods for drying moistened insulation used in VSZhD locomotive depots are listed, and the characteristics of each method are given. Methods: the method of statistical data and analytical review of the current state of the process of drying the insulation of traction rolling stock was applied. Results: the article lists the studies, experiments and results that evaluate the existing methods and methods of insulation drying processes on rolling stock. An updated method of three-cycle drying of moistened insulation of electrical machines has been developed, which is based on the use of electric heating units and provides for oscillatory energy supply. The task has been set to solve the optimal methods for removing moisture from the insulation of traction motors of electric locomotives based on the use of the convective method. Practical importance: based on the conducted research, the possibility of using the proposed three-cycle method for drying moistened insulation of electrical machines has been confirmed, which allows reducing energy costs for repairs and the time of the insulation drying process.

A Fault Prediction Method for Secondary Electric Power Equipment Based on Multi-Round Undersampling Random Forest

Abstract It is necessary to predict the fault states of the large number of power secondary equipment using intelligent methods. However, when compared to large-scale equipment, the number of negative samples representing faulty equipment is significantly smaller than the number of positive samples representing normal equipment. This leads to a pronounced imbalance between positive and negative samples in the task of fault prediction. In this paper, we propose a multi-round undersampling random forest method to predict the fault situations of secondary electric power equipment. First, we collect data from historical power system logs to build the dataset for power secondary equipment and preprocess it. The undersampling method is utilized to generate a balanced dataset of secondary power equipment with a smaller sample size. We generate multiple balanced datasets through rounds of random undersampling without replacement to train multiple random forest models. Subsequently, we predict fault situations in secondary electric power equipment through comprehensive decision-making by these multiple random forest models. We employ a real dataset from the power system of Chongqing, China, for experimental validation. The results demonstrate the superiority of our method over other machine learning prediction models used for comparison.

Deep learning model for detection of hotspots using infrared thermographic images of electrical installations

Hotspots in electrical power equipment or installations are a major issue whenever it occurs within the power system. Factors responsible for this phenomenon are many, sometimes inter-related and other times they are isolated. Electrical hotspots caused by poor connections are common. Deep learning models have become popular for diagnosing anomalies in physical and biological systems, by the instrumentality of feature extraction of images in convolutional neural networks. In this work, a VGG-16 deep neural network model is applied for identifying electrical hotspots by means of transfer learning. This model was achieved by first augmenting the acquired infrared thermographic images, using the pre-trained ImageNet weights of the VGG-16 algorithm with additional global average pooling in place of conventional fully connected layers and a softmax layer at the output. With the categorical cross-entropy loss function, the model was implemented using the Adam optimizer at learning rate of 0.0001 as well as some variants of the Adam optimization algorithm. On evaluation, with a test IRT image dataset, and a comparison with similar works, the research showed that a better accuracy of 99.98% in identification of electrical hotspots was achieved. The model shows good score in performance metrics like accuracy, precision, recall, and F1-score. The obtained results proved the potential of deep learning using computer vision parameters for infrared thermographic identification of electrical hotspots in power system installations. Also, there is need for careful selection of the IR sensor’s thermal range during image acquisition, and suitable choice of color palette would make for easy hotspot isolation, reduce the pixel to pixel temperature differential across any of the images, and easily highlight the critical region of interest with high pixel values. However, it makes edge detection difficult for human visual perception which computer vision-based deep learning model could overcome.

Multivariate impedance spectroscopy method for the measuring of quality and status of electric power oils

With the rapid development of power technology and the complexity of power system equipment, efficient and accurate assessment of the quality and condition of electric power equipment oil (EPEO) has become particularly critical. EPEO is an important factor to ensure the stable operation of power equipment, and its quality and state directly affect the safety and reliability of equipment. However, there are many challenges with traditional oil measuring techniques, which often rely on destructive testing, which not only increases maintenance costs, but can also cause damage to the equipment itself. In the face of these limitations, there is an urgent need to study new oil detection technologies and methods to meet the high standards of modern power systems for high efficiency, non-destructive and comprehensive analytical capabilities. In this paper, a new EPEO measuring technique based on multivariable impedance spectroscopy (MIS) is proposed. Through in-depth analysis of oil's impedance response characteristics under electric field excitation with different frequency., a new approach is provided for the comprehensive evaluation of oil's performance. MIS technology not only has the characteristics of non-destructive testing, ensuring the non-destructive measuring of EPEO, but also its rapid response and real-time analysis ability significantly improves the monitoring efficiency. Based on the proposed MIS detection method, a detection system and experimental prototype which can detect and evaluate the performance and quality of power oil more accurately are designed. Compared with the traditional measuring device, the measuring device utilized in this method can employ three variables. Specifically, it covers a frequency range for the detectable excitation signal spanning from 1 to 100 kHz, an amplitude range from 0.1 to 11.7 V, and a temperature range from −100 °C to 100 °C. The MIS detection method has the capability to identify a variety of parameters, including the dielectric constant, volume resistivity, and dielectric loss factor, among others. This method encompasses a broader spectrum of parameters compared to traditional detection methods, which typically focus on one or two detectable indicators. The correctness and feasibility of the proposed multivariable impedance spectrum detection technique are verified, which provides a new way for the comprehensive evaluation of oil's performance.

Взаимосвязь инновационных и классических методик профессиональной направленности обучения физике в техническом вузе

The introduction of two forms of conducting a laboratory workshop in physics for students for engineering and technology studies in the sphere of marine heat and power engineering, electrical equipment and automation means is considered to the process of studying at the Federal State Budget Educational Institution of Higher Education “Astrakhan State Technical University”. The possibility of developing students' working skills in natural conditions with industrial devices and an engineering approach taking into account the multifactorial conditions of the experiment as an independent work in the framework of the workshop of technical creativity Applied Physics organized at the Department of General Engineering Disciplines and Ground Transport is shown. The formation of the professional orientation of interdisciplinary connections of students of the specialty Thermal Power Engineering and Heat Engineering is illustrated by the example of the development of the laboratory work Determination of the specific heat capacity of metals. The advantages of virtual laboratory work and the possibility of their use on the educational portal of the “Astrakhan State Technical University”, built on the Moodle virtual learning environment, are examined. An example of creating a virtual laboratory work Studying the law of conservation of momentum is considered. It is theoretically proved that the introduction of these types of work into the educational process in physics contributes to the optimally effective formation of general professional competencies and the professional orientation of students' education. The importance of introducing these types of laboratory work into the educational process of physics at the university for the development of students' analytical abilities, creativity and innovation, which is a prerequisite for studying of modern engineers in demand in the labor market in a rapidly changing world, is shown.

A Study on Dielectric Breakdown Properties of Hot CO2/O2/C5F10O Gas Mixture: Focus on Concentration Rate of O2 Gas

A gaseous mixture of CO2 and C5F10O has been widely investigated as one of the alternative gases for SF6. Due to the better electron attachment ability of oxygen molecule O2, it is generally expected that adding of O2 gas would improve the dielectric strength of arc quenching and insulating gas for electric power equipment. Therefore, in this paper, the dielectric breakdown properties of hot CO2/O2/C5F10O gas mixture were numerically estimated. The calculation results revealed that the critical electric field strength of the CO2/C5F10O gas mixture is disappointingly decreased by the addition of O2 gas, especially in the temperature range of 3000 K to 1000 K. This is brought about by the increase of ionization reaction of CO2 molecules with an increase in the O2 concentration in the arc‐quenching gas of CO2/O2/C5F10O. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

ОСНОВНІ РЕЖИМИ РОБОТИ І ГРАФІЧНИЙ ІНТЕРФЕЙС КОРИСТУВАЧА КОМПЛЕКСУ ДЛЯ ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ МАГНІТНИХ ПОЛІВ І ДІАГНОСТУВАННЯ ЕЛЕКТРОЕНЕРГЕТИЧНОГО ОБЛАДНАННЯ

Hardware and software monitoring complex is designed to study the relationship between changes in the patterns of the magnetic field intensity distribution with power equipment failures. In experimental studies with predetermined techni-cal faults artificially introduced into the object the complex will provide useful and reliable results by registering changes in the magnetic field induction in the spatial, temporal and frequency domains. The choice and flexible adjust-ment of data collection tools by the researcher will ensure the use of the most appropriate method for measuring, con-verting and displaying information about the investigated faults. The article presents the main operating modes and graphical user interfaces of a personal computer and a mobile data acquisition system that jointly convert, store, ana-lyze and display measurement information received from various magnetic sensors. The generalized functional specifi-cation of the complex software, the design of the graphical user interface (GUI) as parts of the real-time operating sys-tem (RTOS) of the mobile data acquisition system (DAQ) and PC software will also be used in the development of prob-lem-oriented computer diagnostic systems for electric power equipment. Ref. 12, fig. 3.

Object detection algorithm for indoor switchgear components in substations based on improved YOLOv5s

With the continuous progress of science and technology, electric power equipment detection systems are developing in the direction of artificial intelligence. To achieve good automatic detection results, a high-quality and speedy algorithm is designed to intelligently detect indoor switchgear components in substations. This proposed method can detect the status of components based on image processing technology, which belongs to the field of condition monitoring. In this paper, the targets to be detected include multi-colour buttons or lights and the ammeters or voltmeters of the electrical switchgear. Two hybrid improved algorithms are used to optimise the you only look once v5s (YOLOv5s) network framework for increasing the detection speed and performance. Firstly, deeper feature map extraction is achieved using HorNet recursive gated convolution to replace the original C3 module for more efficient results. Then, a bidirectional feature pyramid network (BiFPN) algorithm is used to achieve the bidirectional propagation of feature information in the feature pyramid. This method can promote better fusion of feature information at different levels and help to convey feature and location information in the image. Finally, the improved YOLOv5s-BH model is used to detect the targets in substations. The experimental results show that the proposed method provides encouraging detection results for indoor switchgear components in substations.

TGLFusion: A Temperature-Guided Lightweight Fusion Method for Infrared and Visible Images.

The fusion of infrared and visible images is a well-researched task in computer vision. These fusion methods create fused images replacing the manual observation of single sensor image, often deployed on edge devices for real-time processing. However, there is an issue of information imbalance between infrared and visible images. Existing methods often fail to emphasize temperature and edge texture information, potentially leading to misinterpretations. Moreover, these methods are computationally complex, and challenging for edge device adaptation. This paper proposes a method that calculates the distribution proportion of infrared pixel values, allocating fusion weights to adaptively highlight key information. It introduces a weight allocation mechanism and MobileBlock with a multispectral information complementary module, innovations which strengthened the model's fusion capabilities, made it more lightweight, and ensured information compensation. Training involves a temperature-color-perception loss function, enabling adaptive weight allocation based on image pair information. Experimental results show superiority over mainstream fusion methods, particularly in the electric power equipment scene and publicly available datasets.

High-temperature properties of dry air used as arc quenching medium and its mixture with vaporized C2F4 : reaction products and critical reduced electric field strength at 300–3000 K

Recently, electric power equipment manufacturers released a joint statement with the aim of developing high-voltage electrical equipment completely free of fluorinated gases such as fluoroketones and fluoronitriles, which are considered as alternatives to SF6 and artificially produced compounds of F. This paper considers air as a typical gas present naturally in the environment to investigate its high-temperature properties, including an air mixture with C2F4 vapor injected from a polytetrafluoroethylene nozzle, for application as an arc-quenching medium in a high-voltage circuit breaker equipped with a nozzle. Chemical composition results for the reaction products at 300–3000 K show that the admixture of C2F4 vapor causes a decrease in the molar number of O2 contained in the air, owing to the production of O-containing compounds such as CO2 and CO . Additionally, the results reveal that the admixture of C2F4 vapor lead to the production of CF4 as the predominant F-containing compound. Furthermore, the boundary condition for O2 production in terms of O2 molar number XO2 and C2F4 molar number XC2F4 is formulated. Such evaluation of the mixture composition enables the determination of a reduced effective collision ionization coefficient αˉ/N and a critical reduced electric field strength Ecr/N , resulting in αˉ/N = 0. The strength Ecr/N for the mixture with 30%–100% C2F4 molar fraction rises to approximately 150 Td (1 Td = 1 ×10−21 V m2) over 300–3000 K, which is 20–50 Td higher than that for high-temperature air unmixed with C2F4 vapor. The variation in Ecr/N is discussed in terms of predominant electron impact processes and the electron energy distribution function in the mixture.

Superior thermal transport and electrically insulating properties of epoxy composites with waxberry-like calcined alumina/poly diallyldimethylammonium chloride/diamond

This work reported a novel preparation of waxberry-like calcined alumina/poly diallyldimethylammonium chloride/diamond (AO*@ND) via a facile self-assembly of cationic polymer, electrostatic adsorption of nano-sized diamonds and calcination process. The incorporation of hybrid particles into an epoxy matrix significantly enhanced the thermal conductivity and dielectric properties. For example, the thermal conductivity of epoxy composite with 10 wt% calcined AO*@ND in air at 500 °C soars to a remarkable level of 0.70 W/(m·K) and 1.83 W/(m·K) at room temperature and 100 °C, respectively. In addition, its dielectric breakdown strength was 59.6 kV/mm, only showing a decrease of 11 % compared to that of epoxy. More importantly, the epoxy composites with the calcined AO*@ND showed an ultralow dielectric loss. The modification strategy of hybrid filler provides a new insight on the development of thermally conductive yet electrically insulating materials for future power modules and electrical equipment.

Molecular simulation study on the influence mechanism of thermal and mechanical properties of boron nitride filled epoxy resin

Epoxy resin (EP) is used in electric power equipment due to its superior mechanical and insulating qualities. However, as power equipment advances towards high voltage and high frequency, the drawbacks of epoxy resin’s poor thermal conductivity become more apparent. This study studied the thermal and mechanical properties of an EP composite when the concentration of hydroxylated boron nitride (BN) was increased. The findings demonstrate that as BN content is increased, epoxy resin’s thermal conductivity also increases. When BN concentration reaches 40%, the heat conduction network is constructed. The mechanical characteristics of epoxy resin rapidly deteriorate and BN agglomeration occurs when the concentration exceeds this threshold. Better dispersion of the hydroxylated BN is made possible by the hydrogen bond formed between BN and epoxy resin, which regulates the mechanical properties of the EP.

An Investigation of The Impact of Carbon Emission Factor Selection on Carbon Accounting of Electric Power Equipment

With the implementation of China’s carbon peaking and carbon neutrality goals, the power industry as a key industry urgently needs to carry out comprehensive carbon accounting work. Carbon accounting of electric power equipment is an important part of carbon accounting in electric power industry. In the process of carbon accounting for electric power equipment, different carbon emission factors may lead to different final accounting results. Based on this, this paper calculates the carbon emission factors of two main raw materials required for the production of electric power equipment in different regions and different years, and applies them to the carbon footprint calculation of SFPZ-240,000/330 transformer. According to the above results, the influence of carbon emission factor selection on carbon accounting of electric power equipment is analyzed.

On the issue of applying the dynamic thermal rating in electric power distribution system

The article considers separate studies and review articles on dynamic thermal rating system in power transmission lines and electrical equipment. Available researches of foreign authors are mainly devoted to forecasting algorithms, model-ing methodologies and implementation of dynamic thermal rating in order to increase the capacity of power transmis-sion lines. It is shown that for the tasks of planning and management of the electric power system in Russia, the need to study and coordinate domestic and foreign developments on the assessment of the capacity of power transmission lines and power distribution is currently relevant. The expansion of residential areas increases the load on electric distribution network due to the shift of maximum power consumption. The currently dynamically changing conditions of electricity consumption direct attention to the development of new technological concepts and the applicability of the existing approaches to assessing the capacity of electricity transmission lines to distribution networks. Available research on dynamic thermal rating in electric distribution networks has focused much attention on both the potential problems and benefits of its implementation in the integration of distributed generation based on the renewable energy sources, in particular wind generation. The ambiguous impact of dynamic thermal rating systems on the reliability of the electric distribution network and the need for their reasonable use, as well as a significant lack of research in relation to cable distribution networks and consistency in assessing their capacity depending on the cable insulation material are being not-ed. Few studies have verified the adaptation of the state-of-the-art approach of dynamic thermal rating of overhead transmission lines to cable lines for predicting parameters corresponding to operational objectives. The research results can be useful in the development and modernization of metering systems, in which new functions of power loss moni-toring and automated determination of distribution network reliability indicators are implemented, which will allow, within the framework of “smart grids”, to ensure the required level of reliability of power supply to consumers.