Current Transformer Research Articles

A Power Quality Assessment of Electric Submersible Pumps Fed by Variable Frequency Drives under Normal and Failure Modes

This paper proposed a simplified modeling approach for a power quality (PQ) assessment of Electric Submersible Pumps (ESP) systems supplied by the two-level, the neutral-point-clamped three-level, and the cascaded H-bridge (CHB) multilevel inverter VFD topologies. The VFD switching function models and their analytical expressions are proposed to understand how they can create high-frequency components that might excite the resonance mode in a transmission cable or a rotating shaft system. Voltage, current, and motor airgap torque harmonics induced by each VFD topology in a balanced operation mode are derived and correlated to the PWM carrier and motor operating frequencies. The motor airgap harmonics are calculated based on Concordia’s transformation of voltages and currents in αβ-plan. These harmonic components are represented in the form of Campbell diagrams. An analysis of harmonics under unbalanced conditions was also conducted in a CHB VFD topology-powered ESP system with failed and bypassed cells. The investigated modulation technique is a neutral-shift PWM method that enables the system to operate balanced line-line voltages even if the line-neutral voltages are unbalanced. The effects of modifying the electrical spectrum using the neutral-shift PWM method on electrical and mechanical spectra are analyzed. The results of the Matlab/Simulink-based simulation show that the proposed full ESP system model is highly accurate in both normal and failure modes. The results are consistent with theoretical predictions and are graphically shown in the time and frequency domains for easy analysis. Hybrid experimental–numerical results on a reduced-scale laboratory setup are also discussed to confirm the correctness of the suggested developments.

Modelling and Experimental Investigation on the Differential Protection of Transmission Line

Due to the significant impact of the fault on power systems and the failure of protection devices, power system operators and researchers have given reliability a great deal of consideration. The modern IEC 61850 standard is used recently to improve communication systems in digital substations and allow signals to be shared between the devices. Differential protection is used to protect the transmission lines, cables, and transformers, as it detects the faults by comparison of the currents flowing into and out of the protected devices. In this research, MATLAB/Simulink has been utilized to simulate the differential protection by using two current transformers (CTs) and to analyze the current waveforms of CTs. A model of the transmission line has been implemented in Taylor’s University Lab to validate the simulation results and measure the differential current, which equals the current summation of two CTs. The outcomes of the research show that the phase shift in the secondary side of CTs between two terminal points is zero and the value of differential current is zero under normal operating situations. However, the differential current has increased in each of the following cases: one CT is connected to the system with the wrong polarity or under an internal fault.

AC Series Arc Fault Detection Based on RLC Arc Model and Convolutional Neural Network

AC series arc faults in the power system can lead to electrical fires. However, the generalization performance of the determined detection method would be affected under unknown loads, as current features vary with loads. To address this issue, this paper presents a series arc fault detection method based on a high-frequency (HF) RLC arc model and one-dimensional convolutional neural network (1DCNN). By the current transformer used for receiving differential HF features (D-HFCT), current with complex features is firstly simplified and divided into different oscillation-signal types. Since the types of real D-HFCT data are limited, the RLC arc model is used to generate D-HFCT data with various types of oscillation features by adjusting load types, initial phase angles and Bernoulli-sequence frequencies. Then, the simulated data are adopted to train the 1DCNN model. Finally, the trained 1DCNN model can detect series arc faults under different types of real loads. Compared with the 1DCNN method driven by the limited types of real-current data, the presented method shows good generalization ability and achieves 99.33% average detection accuracy under nine types of unknown loads, which benefits from the training of simulated D-HFCT data with abundant HF oscillation features.

Three‐phase current reconstruction method for permanent magnet synchronous motor based on current transformer sensors

AbstractThe position sensorless permanent magnet synchronous motor (PMSM), with its simple structure, is applied in the aerospace field with high reliability requirements. To drive PMSM safely, the three‐phase current measured from the driver needs to be isolated for the closed‐loop control. And then, the accuracy current measurement is crucial for achieving optimal motor performance. In the paper, current transformer (CT) with centre taps is employed to isolate and measure the high‐frequency current of the inverter switch. Additionally, an algorithm is proposed to reconstruct the switch current into the low‐frequency phase current. Subsequently, the measuring method and the algorithm are applied to an inverter platform, which drives a 100W PMSM. Finally, the reconstructed phase current waveform is compared with the measured phase current waveform, and the experimental results show that the above method is effective and feasible.

Transformation of ecosystems in Bryansk Oblast caused by the agro-industrial complex development

The article outlines the location, scales, and intensity of the current ecosystems transformation due to operation of the agro-industrial complex industries in Bryansk Oblast of the Russian Federation. By means of official statistic data and space images gathered from open sources, the key factors determining the environmental condition of agricultural landscapes are identified. For each agricultural landscape’s units, a detailed description is given. Analysis of the current environmental situation within these units is also conducted. It was determined that over the last 12 years, the severe level of ecosystems transformation has been forming in the central and eastern parts of agricultural lands. The significant level of ecosystems transformation is observed in the north, as well as in the eastern and southwestern parts. The moderate level of ecosystems transformation is mostly common on the western part and is located in the central and eastern parts of agricultural lands. The minor level of ecosystems transformation is typical for the south-central and for the north-central parts of agricultural lands. The study shows that the spatial differentiation of the levels of ecosystems transformation in Bryansk Oblast is strongly determined by environmental conditions, the structure of natural landscapes, and depends on the specifics of agriculture.

FINANCIAL INCLUSION AS A STRATEGIC AXIS TO ENHANCE FINANCIAL STABILITY IN LIGHT OF THE CURRENT TRANSFORMATIONS - MODELS FROM ARAB COUNTRIES –

This study aims to highlight the most important recent global transformation in the financial and banking sphere financial inclusion ", which was revealed by the 2008 global financial crisis, financial inclusion is a tool that contributes to the delivery of banking services to all segments of society, especially marginalized groups at low cost. and thus, poverty reduction, in addition, to being an important input for the promotion of financial stability, which is an essential strategic objective as it has received considerable attention from field professionals recently, and it has taken the center stage in Government, financial and economic bodies, particularly in the Arab countries. This study is also particularly important because financial inclusion is regarded as a strategic focus for enhancing financial stability, especially given the current challenges and shifts in the world's technological field within the framework of the financial and banking sphere to promote the economies of the Arab countries. The study seeks to respond to the following problems: To what extent can financial inclusion contribute to enhancing financial stability in the current financial transformations in the Arab countries?.

Maximum Overcurrent Protection of Electrical Installations with Remote Selection of Settings

This paper presents that one of the urgent tasks of the modern electric power industry is to build current protections for electrical installations that do not use current transformers with ferromagnetic cores. It is shown that magnetically controlled inductance coils can be used to build such protections, installing them near the current-carrying buses of the electrical installation, as they have important advantages for relay protection in comparison with other magnetically controlled elements: they do not need temperature compensation devices, can simultaneously perform the functions of analog-discrete converter, measuring converter and measuring protection body. The considered overcurrent protection (overcurrent protection) of electrical installations has positive characteristics in comparison with traditional overcurrent protections, made with the use of current transformers and current relays with ferromagnetic cores. The result is the creation of resource-saving current protections made on inductance coils to protect electrical installations. A new design of current protection on inductance coils with remote selection of its settings for electrical installations connected to a the switchgear cell of a complete switchgear (CCS) is proposed. The maximum current protection with the presented implementation scheme, once again confirms the possibility of building current protections for the various electrical installations connected to the switchgear, with the installation of an inductance coil inside the switchgear. The use of the presented protection increases t

JAPAN’S VALUE-BASED RELATIONSHIP IN ACTION: THE CASE OF CENTRAL ASIA

In light of continuing geopolitical and geoeconomic transformations in Eurasia, regional and international players are revising their foreign policies toward Central Asia. Japan, which has been developing stable and value-oriented cooperation with the region, has also been affected by the current transformations that impact the relationship with Central Asia. The paper attempts to reintroduce Japan’s vision of Central Asia by unpacking Japan’s larger matrix of foreign policy and scrutinising its humanitarian and development assistance efforts in Central Asia. The paper first focuses on the retrospective developments of Japan’s engagement with the region. Then it discloses the economic underpinnings of cooperation. Further, discuss development assistance mechanisms in Central Asia. In conclusion, the paper summarises Japan’s engagement with Central Asia in connection to previous and ongoing political and economic developments in the region. By doing so, another perspective on Japan-Central Asia affairs will be provided that enables scientific discussions on Japan’s transforming foreign policy.

A Ginseng Appearance Quality Grading Method Based on an Improved ConvNeXt Model

In order to solve the problem of the small degree of variability between the features of ginseng grading classes and the resulting need for heavy reliance on professionals, this study established a ginseng dataset containing 5116 images with three classes in different contexts and proposed a ginseng-grading model based on an improved ConvNeXt framework. Firstly, a Channel Shuffle module was embedded in the backbone network after down-sampling to fully fuse the channel features and improve the model’s grading accuracy. The model’s characterization ability enriched the feature space of the convolutional block and further improved the model’s accuracy. Finally, the original activation function, GELU, was replaced with the PreLU activation function to increase the nonlinear variability of the neural network model and improve the model’s accuracy and efficiency. The experimental results show that the method demonstrated accuracy improvements of 2.46% and 4.32%, respectively, compared with the current advanced networks, Vision Transformer and Swim Transformer. Furthermore, the accuracy, precision, recall, and specificity of ginseng classification reached values of 94.44%, 91.58%, 91.04%, and 95.82%, respectively, and the loss rate was reduced to 0.24. A comparison with expert appraisal results showed high consistency, thus verifying our model’s accuracy and reliability in ginseng quality assessment and its ability to provide technical support for intelligent ginseng quality grading.

Policy on Development of S&T Information in the Current Digital Transformation Context

The article analyzes the role of science and technology (S&T) information and development policies, the relationship between information and policy, and a number of macro policies on S&T information. From that, the study proposes policies for the development of S&T information in the context of the current digital transformation.

A Wide-Band Modeling Research of Voltage Transformer in EMU

Considering that current voltage transformer models of electrical multiple units (EMUs) are narrow-band models or transformer models, this paper introduces a wide-band model of EMU voltage transformers based on the vector fitting method, circuit synthesis theory and black-box model theory. The admittances of voltage transformers from 30 kHz to 5 MHz are measured by the vector network analyzer, the branch admittances in the pi-type equivalent circuit are calculated according to the equation of a two-port network equivalent circuit. Based on the vector matching method, the rational function formulas of branch admittances are obtained, and the formulas are converted into the circuit models by circuit synthesis theory. The pi-type equivalent circuit model is constructed in the simulation software, and so is the voltage transformer model in the range of 30 kHz–5 MHz. The frequency sweeping method is used to measure the transmission characteristics from direct current (DC)to 30 kHz. The pi-type model is modified according to transmission characteristics, whereby the wide-band model in DC-5 MHz is obtained. Fast pulse experiments are carried out on the voltage transformer, and the actual injected fast pulse voltage is used as the excitation source in the simulation model. The measurement and simulation results on the secondary side of the voltage transformer show that the wide-band model has a high accuracy.

New Synthetic Partial Discharge Calibrator for Qualification of Partial Discharge Analyzers for Insulation Diagnosis of HVDC and HVAC Grids.

A synthetic partial discharge (PD) calibrator has been developed to qualify PD analyzers used for insulation diagnosis of HVAC and HVDC grids including cable systems, AIS, GIS, GIL, power transformers, and HVDC converters. PD analyzers that use high-frequency current transformers (HFCT) can be qualified by means of the metrological and diagnosis tests arranged in this calibrator. This synthetic PD calibrator can reproduce PD pulse trains of the same sequence as actual representative defects (cavity, surface, floating potential, corona, SF6 protrusion, SF6 jumping particles, bubbles in oil, etc.) acquired in HV equipment in service or by means of measurements made in HV laboratory test cells. The diagnostic capabilities and PD measurement errors of the PD analyzers using HFCT sensors can be determined. A new time parameter, "PD Time", associated with any arbitrary PD current pulse i(t) is introduced for calibration purposes. It is defined as the equivalent width of a rectangular PD pulse with the same charge value and amplitude as the actual PD current pulse. The synthetic PD calibrator consists of a pulse generator that operates on a current loop matched to 50 Ω impedance to avoid unwanted reflections. The injected current is measured by a reference measurement system built into the PD calibrator that uses two HFCT sensors to ensure that the current signal is the same at the input and output of the calibration cage where the HFCT of the PD analyzer is being calibrated. Signal reconstruction of the HFCT output signal to achieve the input signal is achieved by applying state variable theory using the transfer impedance of the HFCT sensor in the frequency domain.

Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medium-voltage sensor is compared with that of a reference PT and a CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the U.S. Department of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with an integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that is used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, and service restoration), while the analog signals are recorded by the same high-resolution power meter. The behaviors of analog signals, harmonic components, total harmonic distortion, and crest factors are assessed for this power line sensor and compared with those of the reference PT/CT because of the absence of testing standards for advanced outdoor power line sensors.

Fine-Grained Position Helps Memorizing More, a Novel Music Compound Transformer Model with Feature Interaction Fusion

Due to the particularity of the simultaneous occurrence of multiple events in music sequences, compound Transformer is proposed to deal with the challenge of long sequences. However, there are two deficiencies in the compound Transformer. First, since the order of events is more important for music than natural language, the information provided by the original absolute position embedding is not precise enough. Second, there is an important correlation between the tokens in the compound word, which is ignored by the current compound Transformer. Therefore, in this work, we propose an improved compound Transformer model for music understanding. Specifically, we propose an attribute embedding fusion module and a novel position encoding scheme with absolute-relative consideration. In the attribute embedding fusion module, different attributes are fused through feature permutation by using a multi-head self-attention mechanism in order to capture rich interactions between attributes. In the novel position encoding scheme, we propose RoAR position encoding, which realizes rotational absolute position encoding, relative position encoding, and absolute-relative position interactive encoding, providing clear and rich orders for musical events. Empirical study on four typical music understanding tasks shows that our attribute fusion approach and RoAR position encoding brings large performance gains. In addition, we further investigate the impact of masked language modeling and casual language modeling pre-training on music understanding.

DeMT: Deformable Mixer Transformer for Multi-Task Learning of Dense Prediction

Convolution neural networks (CNNs) and Transformers have their own advantages and both have been widely used for dense prediction in multi-task learning (MTL). Most of the current studies on MTL solely rely on CNN or Transformer. In this work, we present a novel MTL model by combining both merits of deformable CNN and query-based Transformer for multi-task learning of dense prediction. Our method, named DeMT, is based on a simple and effective encoder-decoder architecture (i.e., deformable mixer encoder and task-aware transformer decoder). First, the deformable mixer encoder contains two types of operators: the channel-aware mixing operator leveraged to allow communication among different channels (i.e., efficient channel location mixing), and the spatial-aware deformable operator with deformable convolution applied to efficiently sample more informative spatial locations (i.e., deformed features). Second, the task-aware transformer decoder consists of the task interaction block and task query block. The former is applied to capture task interaction features via self-attention. The latter leverages the deformed features and task-interacted features to generate the corresponding task-specific feature through a query-based Transformer for corresponding task predictions. Extensive experiments on two dense image prediction datasets, NYUD-v2 and PASCAL-Context, demonstrate that our model uses fewer GFLOPs and significantly outperforms current Transformer- and CNN-based competitive models on a variety of metrics. The code is available at https://github.com/yangyangxu0/DeMT.

MANAGEMENT OF TEACHING EQUIPMENT IN PRIMARY SCHOOLS IN CLUSTER 3, PHU LY CITY, HA NAM PROVINCE IN THE CONTEXT OF DIGITAL TRANSFORMATION

The position of teaching equipment in the current digital transformation context is not only a means of active support for the implementation of content and innovation of teaching methods, but also a means of providing new knowledge to students. In order to meet the requirements of innovation in program content and teaching methods, it is necessary to increase the effective use of teaching equipment, especially modern teaching equipment. Teaching equipment is especially important for elementary students because it helps them observe things and phenomena visually, helping students to understand more deeply the content of the lesson. This article evaluates the current situation of teaching equipment management in primary schools in cluster 3, Phu Ly city, Ha Nam province in the context of digital transformation, analyzing strengths and weaknesses, subjective and objective causes from which, 6 measures to effectively manage teaching equipment in primary schools in cluster 3, Phu Ly city, Ha Nam province are proposed in the current digital transformation context.

Exploring the Road of Digital Transformation of Agricultural Marketing Based on the Perspective of Platform Economy

In order to meet the trend of digital transformation and build a marketing system for agricultural products in the form of platform economy, this paper adopts the literature research method to analyze the coupling of the two concepts of platform economy and agricultural products marketing under the framework of digital transformation, and explain the immaturity of marketing subjects, non-standardized marketing channels, unsuitable logistics system, unsuitable marketing products and unclear marketing rules under the current digital transformation mode of agricultural products marketing. The problems of quality assurance and unclear marketing rules. As a result, this paper puts forward policy suggestions, namely, taking the government as the leader, actively exploring new thinking, new ideas and new roads for digital transformation of agricultural products on the basis of improving the legal system, and building a standardized, extensive and innovative Internet agricultural products marketing platform by strengthening the training for relevant practitioners.

Feasibility analysis of new green liquid dielectrics for transformers

The insulating ingredient of the traditional transformer is a mineral oil with low combustibility and biodegradability. As a result, it is unsuitable for current and future transformer applications. Furthermore, finding fossil fuels is becoming increasingly difficult. As a result of the aforementioned limitations, there is a need to look for a replacement shielding oil. This study analysed the crucial characteristics of two biodegradable oils – namely, olive and palm oils – against worldwide standards. In addition, a 1 kVA transformer was subjected to a load test using olive and palm oils in place of traditional insulating solutions to assess their practical feasibility. The authors also looked into the technical feasibility of making a percentage-based blend. According to study results, vegetable oil is a choice superior to mineral oil for electrical and fire protection. However, the density of vegetable oil is substantially higher than that of mineral oil. As a result, the cooling tube of a transformer must be carefully considered throughout its construction. Vegetable oils also have a higher concentration of lipids with a higher molecular weight. The load test revealed that palm oil performs better than mineral oil and olive oil as a liquid dielectric. Furthermore, palm oil with a higher concentration of mineral oil provides properties superior to those of others.

Review of Reinventing martial arts in the 21st Century, by George Jennings

In Reinventing martial arts in the 21st Century (published by Peter Lang, 2023), George Jennings proposes a hybrid online/offline multi-situated ethnography to account for the circumstances of traditional martial arts nowadays. The book is divided in three parts, preceded by an extended an unusual preface about an ethnographic account of the practice of martial arts before, during, and after the COVID lockdown. Parts one and two present different lines of the recent development of traditional martial arts. Part three is clearly different from the other two, offering a well based ethnographic text on the life courses of some martial artists taken as case studies. Along the text, the author poses a well- balanced set of research techniques and sources to ground his analysis. Jennings affords innovative angles to see the current transformation of these cultural practices. Besides, the book points to a myriad of possible directions that the author will surely explore and further develop in future volumes.

Unbalanced Current Identification of Three-Core Power Cables Based on Phase Detection of Magnetic Fields

Identifying unbalanced phase currents is crucial for control and fault alarm rates in power grids, especially in urban distribution networks. The zero-sequence current transformer, specifically designed for measuring unbalanced phase currents, offers advantages in measurement range, identity, and size, compared to using three separate current transformers. However, it cannot provide detailed information on the unbalance status beyond the total zero-sequence current. We present a novel method for identifying unbalanced phase currents based on phase difference detection using magnetic sensors. Our approach relies on analyzing phase difference data from two orthogonal magnetic field components generated by three-phase currents, as opposed to the amplitude data used in previous methods. This enables the differentiation of unbalance types (amplitude unbalance and phase unbalance) through specific criteria and allows for the simultaneous selection of an unbalanced phase current in the three-phase currents. In this method, the amplitude measurement range of magnetic sensors is no longer a critical factor, allowing for an easily attainable wide identification range for current line loads. This approach offers a new avenue for unbalanced phase current identification in power systems.