Circuit Of Transformer Research Articles

Enhanced RF Energy Harvesting System Utilizing Piezoelectric Transformer.

RF energy harvesting converts ambient signals into electrical power, providing a sustainable energy source. This study demonstrates the use of a piezoelectric transformer for efficient RF energy harvesting. In this work, a piezoelectric transformer (PT) is employed as a high-gain, efficient inverting amplifier to enhance RF wireless energy harvesting. The PT, composed of lead zirconate titanate (PZT), is placed after the receiving loop antenna, with its output connected to an AC-to-DC converter circuit. Maximum harvested power was observed at the PT's resonance frequency of 50 kHz, with an optimal load of 40 kΩ. The system, comprising the antenna, transformer, and rectifier circuit, continues to resonate at 50 kHz, as confirmed by input impedance measurements, demonstrating stable and effective performance. The overall system efficiency was characterized to be 88%.

Modeling and transfer characteristics simulation analysis of electronic current transformers

Abstract Compared with conventional electromagnetic current transformers, electronic current transformers have potential transfer advantages to transient current. This paper establishes the equivalent circuits of typical electronic current transformers and constructs transfer functions to analyze their frequency response characteristics. The PSCAD simulation model is established based on the transfer functions to simulate and analyze the transfer characteristics of typical electronic current transformers, and compare them with conventional current transformers in terms of steady-state response, transient response, impulse response, and step response. The analysis results demonstrate that electronic current transformers exhibit superior frequency response and transient response characteristics compared to conventional current transformers. The magnet-optic transformer and fiber-optic current transformer show better performance and are ideal for wide-band current sensing. However, low-power current transformers and Rogowski electronic transformers can only be used for AC measurement as they cannot transfer DC or non-periodic components. The transfer characteristics of fiber-optic current transformers are influenced by closed-loop control loop parameters and need to be designed according to specific application scenarios. The simulation analysis results in this paper can provide guidance for selecting suitable current transformers for new-type power systems.

Low-Cost High-Voltage Power Supply for Hydraulically Amplified Self-Healing Electrostatic Applications

HASEL (Hydraulically Amplified Self-Healing Electrostatic) actuators have gathered momentum in recent years; they are made of very-low-cost materials, making it easy for anyone to develop their own actuators, and they are “soft” and can achieve tasks that are very difficult to complete with traditional rigid actuators, e.g., grasping soft objects. Unfortunately, HASEL actuators are driven by high-voltage (HV) power supplies, which are expensive to control accurately and difficult to scale up for multichannel applications, e.g., prostheses. This paper presents a low-cost HV power supply designed for HASEL applications that generates 2–10 kV DC at 5% of the cost of the existing HV power supplies used in HASEL actuators. At the core of our design, there is a new control strategy based on controlling the charging and discharging of the actuator from the supply’s low-voltage (LV) side rather than switching the HV side with expensive HV optocouplers. Discharge is achieved via a secondary transformer and multiplier circuit, generating a negative HV output capable of discharging the HASEL effectively and safely up to 10 kV.

Определение факта насыщения магнитопровода трансформатора тока на основе непрерывного измерения сопротивления цепи намагничивания

Saturation of electromagnetic current transformers in transient modes of operation of an electric power system can lead to incorrect operation of relay protection devices. One of the most promising directions to improve the stability of the operation of relay protection devices in such modes is digital correction of secondary current. Currently, effective methods have been developed to restore the secondary current based on determination of magnetic circuit saturation. However, the practical application of these methods is impossible due to the imperfection of existing methods of secondary current segmentation. Thus, it is urgent to develop a method to determine saturation for implementation of digital correction algorithms for electromagnetic current transformers. To solve the stated problem, methods of mathematical modeling of electrical circuits containing transformers and the small-disturbance theory have been used. Verification of the research results is carried out in the Matlab software package. A mathematical criterion is formulated to determine the saturation of the magnetic circuit of an electromagnetic current transformer based on the inductance of the magnetization circuit. A method of segmentation of the secondary current has been developed for the implementation of digital correction algorithms based on the proposed criterion. The effectiveness of the developed method to determine the saturation of the magnetic circuit of an electromagnetic current transformer using computational experiments in the Matlab software package is demonstrated. It is planned to verify the developed method using a physical model of an electromagnetic current transformer.

Unsupervised online poor contact detection in the secondary circuit of voltage transformers

Voltage transformers (VTs) are fundamental and crucial instrument devices for accurate voltage measurement. Generally, measurement errors can be caused by both the VT and the secondary circuit. Most research focused on the VT but ignored the secondary circuit between it and the measurement device. Poor contact in the secondary circuit is more challenging to capture than those caused by faulty VTs. In this study, we present an unsupervised online poor contact detection method. It first exploits a time series similarity matrix derived from the measured voltage data. The physical constraints deriving from the electrical topology are utilized to eliminate the non-fault fluctuation. To ensure the versatility of the proposed method, an adaptive threshold determination strategy is designed based on knee point location. Numerical experiments compared with some state-of-the-art methods have validated the effectiveness of the proposed method. The versatility of the proposed method is further validated in three real-world cases.

Inductive Wireless Power Transfer for Autonomous Underwater Vehicles using Split Core Transformer and Resonant LLC Circuit

Unmanned Underwater Vehicles (UUVs) are pivotal for underwater exploration and maintenance. Autonomous Underwater Vehicles (AUVs), with their potential to reduce operational time and environmental impact, are gaining increased interest. However, they face important technological challenges, particularly in power supply. This study focuses into the application of Inductive Wireless Power Transfer (IWPT) for continuous AUV operation, employing tightly coupled split core transformers (SCT) designed for near-field power transfer. Robust isolation and alignment mechanisms are proposed to overcome the effects of seawater environment. An IWPT device with an SCT and resonant LLC circuit is simulated and experimentally tested. Finite Element Method studies highlight the advantage of isolating the device from the seawater environment, especially at high frequencies. LLC simulation and experimental results demonstrate an efficiency in power transfer of 93.2 % and 87.1 %, respectively, transferring up to 312 W. However, global efficiency of the experimental device drops to 76.4 %, highlighting the need for optimizations in circuit design.

Wavelet scattering and multiclass support vector machine (WS_MSVM) for effective fault classification in transformers: a real-time experimental approach

The dependable operation of the protective system is affected by residual magnetism and magnetic bias during the activation of the transformer. Challenges arise in distinguishing between inrush current and fault current when the transformer circuit breaker switching angle and remnant flux attain specific values. This situation can lead to a lack of sensitivity or failure in the operation of the transformer protection system. Thus, this paper proposes an effective approach for classifying different faults in transformers (internal and non-internal faults) using wavelet scattering and multiclass support vector machine (MSVM) technique (WS_MSVM). The wavelet scattering method begins by transmitting the data through a sequence of wavelet transforms, nonlinear operations, and averaging processes. This series of operations aims to generate low-variance representations of time series data. Wavelet time scattering produces signal representations that remain unaffected by shifts in the input signal, while still preserving the ability to distinguish between internal and non-internal faults. Internal faults are those occurring within the zones of the current transformer (CT) connected on both sides of the transformer. On the other hand, non-internal faults consist of magnetizing inrush current, sympathetic inrush current, and external faults (faults occurring outside the CT zones). The efficacy of the proposed WS_SVM is evaluated on the real-time experimental results obtained from the differential path of a laboratory transformer. The experimental data generated over one power frequency cycle under diverse operating conditions is employed in MATLAB to assess the effectiveness of the proposed WS_SVM algorithm.

Research on Winding Dynamic Force and Displacement of Winding in Interturn Short Circuit of Stereo Roll Iron Core Transformer

Abstract The short circuit fault between the turns of the transformer winding accounts for 60% ∼ 70% of the whole winding fault, which seriously adversely impacts the regular functioning of the transformer. This study focuses on analysing the dynamic force and displacement characteristics of the winding in a stereo roll iron core transformer when an inter-turn short circuit occurs. First, a stereo roll iron core transformer finite element model in three dimensions is created. The electromagnetic-solid mechanics coupling method is used to figure out and study the transformer winding’s inter-turn short-circuiting current, leaking electromagnetic field, dynamic force, and displacement distributions. Furthermore, an experimental platform is built to simulate the inter-turn short-circuiting of a stereo roll iron core transformer. The displacement in the time domain and the acceleration in the frequency domain of the winding during the short circuit that occurs between turns will be recorded and analyzed. Finally, it is concluded that under normal working conditions, the winding vibration frequency is between 100 ∼ and 500 Hz. After 19 turns of the short circuit, the winding displacement increases by 32% ∼ 60%, and the high-order harmonic content of the winding vibration frequency increases significantly.

Comparisons of Rice Seed Growths Due to Alternating and Direct Current Electric and Magnetic Field Influences

It is commonly known that electric and magnetic fields of power transmission negatively and positively influence plants. Unfortunately, studies on these influences are minimal, particularly considering the comparison between magnetic field and electric field, on both DC (direct current) and AC (alternating current). This research aims to compare the influences of magnetic field and electric field, both on AC and DC, on rice plant growth. Firstly, prototypes, including the equipment, were constructed to generate AC and DC electric fields using parallel plates of a medium voltage transformer and Cockroft-Walton circuits. Meanwhile, the AC and DC magnetic fields were prepared using three different diameter current-injected coils. The rice seeds were exposed to electric and magnetic fields for one month, with plate distance and coil diameter variations. The results showed that the rice seeds grew differently according to the respective types and magnitudes of the fields. In the first two days, the rice seed growths exposed to electric and magnetic fields were higher than those without field exposures. However, since the thirteenth day, the rice growth rate with field exposure was lower than without. This study also shows that the influences of the DC electric and magnetic fields were more potent than the AC fields. The averages of rice seed growth decreasing rate for the AC and DC electric fields and AC and DC magnetic fields were 0.00827 cm/(kV/m), 0.01167 cm/(kV/m), -0.13267 cm/mT and 1.99005 cm/mT, respectively. As a general suggestion in sites, rice plants should be avoided from a transmission line due to high voltage direct current (DC) rather than that alternating current (AC).

On the question of determining the location of a short circuit on a power transmission line

An algorithm for eliminating aperiodic components from short circuit (SC) currents is proposed. The algorithm is implemented by computer technology and allows you to determine the location of a short circuit and phase loss in 0.5 - 0.6 milliseconds. During such a time interval, saturation of the magnetic circuits of current transformers (CTs) does not occur, and the processors receive undistorted information from the CTs. To implement the algorithm, four measurements of instantaneous current values, separated by equal time intervals (sampling intervals), are sufficient. Elimination of aperiodic components increases the accuracy of determining the location of the fault. The algorithm can be used to determine the location of phase failure, and in digital relay protection based on measuring currents and voltages.

Contribution to the determination of the effect of magnetic storms on the electric power transmission system

Abstract When a magnetic storm hits a power transmission system, quasi-stationary geomagnetically induced currents (GIC) are generated in the high-voltage part of the system. These currents cause semi-saturation of the magnetic circuits of power transformers, which induces current overload in their high-voltage windings and subsequently thermal overload, which can lead to system failures. This rather complex phenomenon was described in [11] by a system of nonlinear differential equations and subsequently solved. This very challenging method is replaced in the present work by a simple approach. It allows not only predicting the imminent danger of system collapse, but gives transformer designers valuable information on how they can counteract this danger.

Resistance values under transformations in regular triangular grids

In Evans and Francis (2022) and Hendel (2021) the authors investigated resistance distance in triangular grid graphs and observed several types of asymptotic behavior. This paper extends their work by studying the initial, non-asymptotic, behavior found when equivalent circuit transformations are performed, reducing the rows in the triangular grid graph one row at a time. The main conjecture characterizes, after reducing an arbitrary number of times an initial triangular grid all of whose edge resistances are identically one, when edge resistance values are less than, equal to, or greater than one. A special case of the conjecture is proven. The main theorem identifies patterns of repeating edge resistances arising in diagonals of a triangular grid reduced s times provided the original grid has at least 4s rows of triangles. This paper also improves upon the notation, concepts, and proof techniques introduced by the authors previously.

Compact Circuits for Efficient Möbius Transform

The Möbius transform is a linear circuit used to compute the evaluations of a Boolean function over all points on its input domain. The operation is very useful in finding the solution of a system of polynomial equations over GF(2) for obvious reasons. However the operation, although linear, needs exponential number of logic operations (around n · 2n−1 bit xors) for an n-variable Boolean function. As such, the only known hardware circuit to efficiently compute the Möbius Transform requires silicon area that is exponential in n. For Boolean functions whose algebraic degree is bound by some parameter d, recursive definitions of the Möbius Transform exist that requires only O(nd+1) space in software. However converting the mathematical definition of this space-efficient algorithm into a hardware architecture is a non-trivial task, primarily because the recursion calls notionally lead to a depth-first search in a transition graph that requires context switches at each recursion call for which straightforward mapping to hardware is difficult. In this paper we look to overcome these very challenges in an engineering sense. We propose a space efficient sequential hardware circuit for the Möbius Transform that requires only polynomial circuit area (i.e. O(nd+1)) provided the algebraic degree of the Boolean function is limited to d. We show how this circuit can be used as a component to efficiently solve polynomial equations of degree at most d by using fast exhaustive search. We propose three different circuit architectures for this, each of which uses the Möbius Transform circuit as a core component. We show that asymptotically, all the solutions of a system of m polynomials in n unknowns and algebraic degree d over GF(2) can be found using a circuit of silicon area proportional to m · nd+1 and circuit depth proportional to 2 · log2(n − d).In the second part of the paper we introduce a fourth hardware solver that additionally aims to achieve energy efficiency. The main idea is to reduce the solution space to a small enough value by parallel application of Möbius Transform circuits over the first few equations of the system. This is done so that one can check individually whether the vectors of this reduced solution space satisfy each of the remaining equations of the system using lower power consumption. The new circuit has area also bound by m · nd+1 and has circuit depth proportional to d · log2 n. We also show that further optimizations with respect to energy consumption may be obtained by using depth-bound Möbius circuits that exponentially decrease run time at the cost of additional logic area and depth.

IoT based monitoring of distribution transformer

As transformer does not have any rotating parts hence it is called as static device, therefore it does not have mechanical losses, but internal stresses arose from abnormal system conditions like Over currents due to overloading on Transformer and short circuits, The faults can cause mechanical and thermal stresses inside the transformer winding and its connecting terminals. Thus transformer must be protected from above stresses. The aim of this project is to obtain real time data of transformer from remote places with the help of Internet of Things[ IOT] and then designing and implementing a Global system of Mobile communication [GSM] based technology to measure overvoltage, load current, and winding temperature. By measuring the condition of Transformer will help us to point out an any abnormalities before any serious damage that in turn leads to a greater credibility and significant cost savings

Comparative analysis of the characteristics of outlet short circuit and winding insulation fault of distribution transformer and its preventive measures

AbstractOutlet short circuit on the low‐voltage (LV) side and winding inter‐turn short circuit faults are hazardous to transformer operation. To investigate the formation mechanism of winding insulation faults of distribution transformer, ANSYS Maxwell was used to build a coupled magnetic field‐circuit model with the same structural dimension as the actual distribution transformer. An outlet short circuit and winding inter‐turn insulation faults were set by using the voltage‐controlled switch in the external circuit of the model. Subsequently, the differences in the electromagnetic characteristics and the electrodynamic force distributions of the windings under three operating conditions, namely, nominal load, three‐phase outlet short circuit on the LV side and inter‐turn insulation failure were studied, respectively. The results show that compared with the rated load, in the cases of outlet short circuit and inter‐turn insulation faults, the amplitude of winding current increases by 20 and 50 times, the magnetic field strength grows by 20 and 17 times, and the electrodynamic force rises by 400 and 230 times, respectively. Outlet short circuit fault is more likely to cause the winding instability and deformation, and inter‐turn short circuit fault can easily burn out winding insulation. Therefore, corresponding preventive measures were proposed.

Parameter estimation in single-phase transformers via the generalized normal distribution optimizer while considering voltage and current measurements

This research addresses, from a perspective of metaheuristic optimization, the problem regarding parametric estimation in single-phase transformers while considering voltage and current measures at the terminals of the transformer and weighing linear loads. Transformer parametric estimation is modeled as a nonlinear problem in order to minimize the mean square error between the calculated voltage and current variables and the measurements taken. The nonlinearities are associated with Kirchhoff's first and second laws applied to the equivalent electrical circuit of the single-phase transformer. The nonlinear optimization problem is solved by applying a metaheuristic optimization algorithm known as the generalized normal distribution optimizer (GNDO), which uses evolution rules that allow exploring and exploiting the solution space via the classical probability function based on normal distributions. Numerical results in three test transformers of 20, 45, and 112.5 kVA demonstrate the effectiveness and robustness of the proposed GNDO approach when compared to other optimizers reported in the literature, such as the crow search algorithm, the coyote optimization algorithm, and the exact solution of the nonlinear optimization model using the fmincon solver of the MATLAB software. All numerical simulations confirm the potential of the GNDO approach to deal with complex optimization problems in engineering and science with promising results and low computational effort.

Development of a simulation model for assessing the technical condition of the magnetic circuit of oil power transformers by measuring the temperature of the tank and the external environment

In the article, the authors analyzed how oil-filled power transformers ensure reliable and stable operation of power transmission systems by providing efficient transmission of electricity of different voltages. In the article, the authors found that the main elements of oil-filled power transformers - the magnetic circuit, the coil and the technical condition of the oil - directly determine the performance of oil-filled power transformers. In this work, a simulation model was developed to evaluate the magnetic circuit of power oil transformers based on the measured temperature of the tank and the external environment during express diagnosis. A simulation model has been developed that allows to calculate the technical condition of oil power transformers operating in city power networks. It is shown that the developed model allows to calculate the value of the technical condition of the oil power transformer with the help of diagnostic parameters. In order to represent the technical state of the magnetic circuit of the oil power transformer, the functions of changing the state value of the output variable in the Mamdani fuzzy logic method are shown and the block diagrams are drawn up. Author’s using the Mamdani fuzzy logic method, express diagnosis of the technical condition of the “Magnetic core of the oil power transformer” was carried out in the Matlab simulink program. During the evaluation, the value of the output parameter is taken from 0 to 100, and each step is divided by 10, the smallest value is 0, and the largest is 100.

Data analysis and calibration of substation monitoring system based on Internet of Things (IoT)

Abstract The complex correlation of multi-source information of power equipment and the efficient validation of data information in the context of the Internet of Things (IoT) of electric power need to be studied urgently. The study applies density clustering to simplify the connection between multidimensional data and proposes a method for detecting anomalies in power equipment states based on interval set theory and density clustering. In addition, to ensure the accuracy of protection and measurement data for secondary equipment in substations, a dual verification system is established to sample secondary equipment data in the station area. The results of the related case study show that the anomaly detection method applying interval set clustering analysis can quickly and effectively detect the state anomalies of power equipment, which can be used as a decision-making basis for power grid troubleshooting. Based on the double calibration system of the guaranteed measurement data, it can realize the functions of power metering device error calibration, a secondary load test of the transformer, a voltage drop test of the secondary circuit of the voltage transformer, and so on.

Perampanel increases seizure threshold in pentylenetetrazole-kindled mice and improves behavioral dysfunctions by modifying mRNA expression levels of BDNF/TrkB and inflammatory markers

Perampanel (PER), a novel 3rd-generation antiseizure drug that modulates altered post-synaptic glutamatergic storming by selectively inhibiting AMPA receptors, is recently approved to treat intractable forms of seizures. However, to date, presumably consequences of long-term PER therapy on the comorbid deleterious psychiatric disturbances and its correlation with neuroinflammatory parameters are not fully investigated in chronic models of epilepsy. Therefore, we investigated the real-time effect of PER on brain electroencephalographic (EEG) activity, behavioral alterations, redox balance, and relative mRNA expression in pentylenetetrazole (PTZ) induced kindling. Male BALB/c mice were pretreated with PER (0.125, 0.25, and 0.5 mg/kg) for 3 weeks and challenged with 11 injections of PTZ at the sub-threshold dose of 40 mg/kg every other day. vEEG from implanted cortical electrodes was monitored to elucidate seizure propagation and behavioral manifestations. Recorded EEG signals exhibited that PER 0.5 mg/kg pretreatment exceptionally impeded the onset of sharp epileptic spike-wave discharges and associated motor symptoms. Additionally, qEEG analysis showed that PER prevented alterations in absolute mean spectral power and reduced RMS amplitude of epileptogenic spikes vs PTZ control. Furthermore, our outcomes illustrated that PER dose-dependently attenuated PTZ-evoked anxiety-like behavior, memory deficits, and depressive-like behavior that was validated by a series of behavioral experiments. Moreover PER, significantly reduced lipid peroxidation, AChE, and increased levels of SOD and total thiol in the mice brain via AMPAR antagonism. Post-PTZ kindling provoked overstimulation of BDNF/TrkB signaling and increased release of pro-inflammatory cytokines that were reversed by PER with suppression of iNOS in brain immune cells. In conclusion, our findings highlight that PER might play an auspicious preventive role in the proepileptic transformation of brain circuits via suppression of BDNF/TrkB signaling and reduced transcriptional levels of neuroinflammatory markers leading to improvised epilepsy-induced neurobehavioral and neurochemical effects.

Modelling the capacitance of the elongated plasma in tokamak

The capacitance model suitable for the non-circular cross-section plasma is studied based on the capacitance model of the circular cross-section plasma. The coaxial elliptic-torus capacitor property is further derived and used to determine the capacity of non-circular cross-section tokamak plasma, such as EAST (Experimental Advanced Superconducting Tokamak). By testing all the physical terms in this model, we find that the capacitance Cp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Cp$$\\end{document}) is increasing exponentially with the increase of elongation ratio (k2/k1), while the minor radius ratio (a2/a1) is just reversed at the flat-top of plasma current, and the capacitance property is implicitly included in the H-mode study during the L–H transition. It is noted that Cp-H mode is the least and Cp-I mode is approximately equal to Cp-L mode under the L-mode, I-mode and H-mode regimes based on this capacitance model in EAST. Consequently, it may be integrated into an equivalent circuit of the tokamak transformer or transport computer code of the edge plasma for use in precise simulations of fusion plasma behavior in the future, such as ITER (International Tokamak Experimental Reactor) or BEST (Burning-plasma Experimental Superconducting Tokamak) in China.