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Funding Information: Financial support was provided by the Swiss National Science Foundation (Grant No. 200021_184940). Funding Information: Networking support provided by the European Cooperation in Science and Technology, COST Action CA19108 (Hi-SCALE) is acknowledged. Funding Information: Supported by Fundação para a Ciência e a Tecnologia, Portugal, with reference UIDB/00066/2020. Funding Information: A part of this work was supported by the Russian National Technology Initiative Foundation (Grant ID 0000000007418QR20002). Funding Information: The research was also supported by the European Synchrotron Radiation Facility (Grant No. MA-2767). Funding Information: This work was supported in part by the New Zealand Ministry of Business, Innovation and Employment (MBIE) by the Strategic Science Investment Fund ‘‘Advanced Energy Technology Platforms’’ under Contract RTVU2004. Funding Information: Y Wang acknowledges support from the National Science Foundation (NSF) Award DMR-2132338. R P Camata and C-C Chen are supported by the FTPP Program funded by NSF EPSCoR RII Track-1 Cooperative Agreement OIA-2148653. C-C Chen also acknowledges support from the NSF Award DMR-2142801. Publisher Copyright: © 2023 The Author(s). Published by IOP Publishing Ltd. This paper presents a roadmap to the application of AI techniques and big data (BD) for different modelling, design, monitoring, manufacturing and operation purposes of different superconducting applications. To help superconductivity researchers, engineers, and manufacturers understand the viability of using AI and BD techniques as future solutions for challenges in superconductivity, a series of short articles are presented to outline some of the potential applications and solutions. These potential futuristic routes and their materials/technologies are considered for a 10-20 yr time-frame. publishersversion published

Characterization of the exact critical current density (Jc) and stress values in twisted superconducting tapes plays an important role for analysing their magnetic, thermal, and mechanical behaviours. In this paper, a model based on Artificial Neural Network (ANN) is introduced to estimate the electro-magneto-mechanical characteristic of different superconducting tapes. For this purpose, magnetic flux density, temperature, strain, total thickness of tape, their width, thickness of stabilisers, and thickness of substrates are used as inputs to ANN model whilst minimum normalised Jc and maximum stress are considered as outputs. The required experimental data are extracted from published papers in literature. The ANN model was trained for Jc/stress estimation using extracted data for different inputs. Sensitivity analysis was conducted on ANN models which were used to estimate the Jc and stress values of tapes, to choose an optimum structure for ANN models to be used in future by other scientists in the superconductivity community. To check the reproducibility, repeatability, and stability of presented results, the estimations with ANN optimum structure were tested for 500 testing runs. We found that the ANN optimum structure was as 1 hidden layer with Levenberg-Marquardt training method and 7 inputs. Comparing to the literature, the proposed ANN model offers about 15% and 1.1% higher accuracy in Jc and stress estimations, respectively.

Resistive type fault current limiters (SFCLs) have attracted lots of attention from research interests and engineering applications, due to their self-triggering, fast and effective fault current limitation ability. Fast recovery of SFCL after quench is highly attractive, yet still remains challenge when recover with load compared to recovering without load. We investigated the dependence of recovery time of a helical SFCL coil on the ratio of prospective current over critical current I pros/ I c. A multilayer simulation model was built in MATLAB/Simulink to investigate the electro-thermal behavior of SFCL coil during a fault and recovery period, and the model was validated by experimental results. Quench simulations were carried out under different I pros/ I c, ranging from 15 to 119 and in different recovery conditions including recovery with load condition and recovery without load condition, while keeping the fault duration of 100 ms. We observed that the SFCL coil reached 85 K and 195 K at the time when the fault was cleared, in the quench tests with I pros/ I c = 15 and 119, respectively. SFCL coil recovered without load in 0.5 s to 10 s, depending on the ratio of I pros/ I c.

More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take advantage of SCs in physics, power engineering, quantum computing, electronics, communications, aviation, healthcare, and defence-related applications. However, there are still challenges that hinder the full-scale commercialization of SCs, such as the high cost of superconducting wires/tapes, technical issues related to AC losses, the structure of superconducting devices, the complexity and high cost of the cooling systems, the critical temperature, and manufacturing-related issues. In the current century, massive advancements have been achieved in artificial intelligence (AI) techniques by offering disruptive solutions to handle engineering problems. Consequently, AI techniques can be implemented to tackle those challenges facing superconductivity and act as a shortcut towards the full commercialization of SCs and their applications. AI approaches are capable of providing fast, efficient, and accurate solutions for technical, manufacturing, and economic problems with a high level of complexity and nonlinearity in the field of superconductivity. In this paper, the concept of AI and the widely used algorithms are first given. Then a critical topical review is presented for those conducted studies that used AI methods for improvement, design, condition monitoring, fault detection and location of superconducting apparatuses in large-scale power applications, as well as the prediction of critical temperature and the structure of new SCs, and any other related applications. This topical review is presented in three main categories: AI for large-scale superconducting applications, AI for superconducting materials, and AI for the physics of SCs. In addition, the challenges of applying AI techniques to the superconductivity and its applications are given. Finally, future trends on how to integrate AI techniques with superconductivity towards commercialization are discussed.

Previous studies on magnetization AC loss of high temperature superconducting (HTS) coated conductors (CCs) taken into account the ideally sinusoidal external magnetic field, or non-sinusoidal by considering only the harmonics in phase with the fundamental component. However, realistically magnetic field often contains harmonics with different phase angles and amplitudes. In this paper, magnetization AC loss in HTS CC was studied, considering the phase angle $\varphi $ of each harmonic; assuming superconductor is subjected to external magnetic field which is distorted by the $3^{\mathrm {rd}}$ and the $5^{\mathrm {th}}$ harmonics. Phase angle of each harmonic was considered in the range of 0 to $\pi $ and amplitude of fundamental magnetic field, was assumed as 10, 20, 50, and 100 mT. Different distortion level of magnetic field was considered too. It is concluded that phase angle of field harmonic has a significant effect on magnetization loss of HTS CCs.

Data-driven models can predict, estimate, and monitor any highly nonlinear and multi-variable behaviour of high-temperature superconducting (HTS) materials, and superconducting devices to analyse their characteristics with a very high accuracy in an almost real-time procedure, which is a significant figure of merit as compared with traditional numerical approaches. The electromechanical behaviour of twisted HTS tapes under different strains, magnetic fields, and temperatures is a complicated problem to be solved using conventional approaches, including finite element-based methods, otherwise, experimental testing is needed to characterise it. This paper aims to offer a data-driven model based on artificial intelligence techniques to predict the electromechanical behaviour of HTS tapes operating under various thermomagnetic conditions. By using the proposed model, normalised critical current value and stress of twisted tapes can be predicted under different temperatures and magnetic flux densities. For this purpose, experimental data were used as inputs to design an adaptive neuro-fuzzy inference system (ANFIS). To achieve the best performance of the prediction system, multiple clustering methods were used, such as the grid partitioning method, fuzzy c-means clustering method, and sub-clustering method. Sensitivity analyses were conducted to find the best architecture of ANFIS to predict and model electromechanical behaviour of twisted tapes with high accuracy.

Current is no longer sinusoidal in modern electric networks because of widespread use of power electronic-based equipments and nonlinear loads. Usually AC loss is calculated for pure sinusoidal current, while it is no longer accurate when current is nonsinusoidal. On the other hand, efficiency of cooling system in large scale power devices is dependent on accurate estimation and prediction of the heat load caused by AC loss in design stage. Therefore, estimation of nonsinusoidal AC loss of high temperature superconducting (HTS) material would be of great interest for designers of large-scale superconducting devices. In this paper, at first nonsinusoidal AC loss of a typical HTS tape was calculated under distorted currents using H-formulation finite element method. Then, a range of artificial intelligence (AI) models were implemented to predict AC loss of a typical HTS tape. In order to find the best and more adaptive AI model for nonsinusoidal AC loss prediction, different regression models are evaluated using Support Vector Machine regression model, Generalized Linear regression model, Decision Tree regression model, Feed Forward Neural Network based model, Adaptive Neuro Fuzzy Inference System based model, and Radial Basis Function Neural Network (RBFNN) based model. In order to evaluate robustness of developed models cross-validation technique is implemented on experimental data. To compare the performance of different AI models, four prediction measures were used: Theil's U coefficients (U_Accuracy and U_Quality), Root Mean Square Error (RMSE) and Regression value (R-value). Obtained results show that best performance belongs to RBFNN based model and then ANFIS based model. U coefficients and RMSE values are obtained less than 0.005 and R-Value is become close to one by using RBFNN based model for testing data, which indicates high accuracy prediction performance.

This article introduces the potential use of superconductivity in cryo-electrified aircraft as the aviation industry and governments move toward zero-emissions environmental targets. It outlines the different electrical insulating materials and discusses potential advantages and disadvantages for cryogenic superconducting applications.

For modelling superconductors, interpolation and analytical formulas are commonly used to consider the relationship between the critical current density and other electromagnetic and physical quantities. However, look-up tables are not available in all modelling and coding environments, and interpolation methods must be manually implemented. Moreover, analytical formulas only approximate real physics of superconductors and, in many cases, lack a high level of accuracy. In this paper, we propose a new approach for addressing this problem involving artificial intelligence (AI) techniques for reconstructing the critical surface of high temperature superconducting (HTS) tapes and predicting their index value known as n-value. Different AI models were proposed and implemented, relying on a public experimental database for electromagnetic specifications of HTS tapes, including artificial neural networks (ANN), eXtreme Gradient Boosting (XGBoost), and kernel ridge regressor (KRR). The ANN model was the most accurate in predicting the critical current of HTS materials, performing goodness of fit very close to 1 and extremely low root mean squared error. The XGBoost model proved to be the fastest method, with training computational times under 1 s; whilst KRR could be used as an alternative solution with intermediate performance.

Fluctuations in the critical current along the length of high-temperature superconducting (HTS) tapes manufactured in the form of coated conductors is a common manufacturing phenomenon. These fluctuations originate in the generation of weak points through the length of HTS tapes that may cause quenching later. By means of the propagation of quenches in HTS tapes, the reliability, stability, and the performance of the device and the system that contain HTS tapes could be seriously degraded. In this study, an artificial intelligence technique based on artificial neural networks (ANN) was proposed to estimate the probability of quenches in HTS tapes caused by weak points. For this purpose, six different HTS tapes were considered with different widths, total thicknesses, and thicknesses of sub-layers. Then, for each one of these tapes, different operating conditions were considered, where the operating temperature changed from 40 K to 80 K, in 1 K steps. Under each operating temperature, different operating currents were considered from 50% to 100% of tape critical current. All of these resulted in more than 5000 different data points. Then, for each of these data points, analytical modelling was performed to provide initial inputs and outputs for the ANN model. It should be noted that the performed simulations were conducted based on an analytical method that was experimentally validated in the literature. After that, a sensitivity analysis was conducted to select the hyperparameters and structure of the ANN-based model. The last step was to take advantage of the trained model, as a function in the MATLAB software package to estimate the probability of quenches in different case studies. The significant feature of the proposed model is the capability for estimating the probability of quenches under different operating temperatures and currents for different types of HTS tapes.

The aim of the presented study is to optimize the different classes of high-temperature superconducting (HTS) DC cables for improving their performances in a cryo-electric aircraft considering their weight, peak temperature during faults, and the ratio of current passing through each tape to the critical current of HTS tapes. These terms were interpreted into three objective functions, and a multi-objective optimization algorithm known as non-dominated sorting genetic algorithm II was used to find the optimal solution clusters. The cable optimization was conducted for different former materials by changing the former thickness and radius. Results showed that the DC HTS cables with aluminum former have the lowest weight while cables with copper formers have the best thermal performance against faults.

Along with advancements in superconducting technology, especially in high-temperature superconductors (HTSs), the use of these materials in power system applications is gaining outstanding attention. Due to the lower weight, capability of carrying higher currents, and the lower loss characteristic of HTS cables, compared to conventional counterparts, they are among the most focused large-scale applications of superconductors in power systems and transportation units. In near future, these cables will be installed as key elements not only in power systems but also in cryo-electrified transportation units, that take advantage of both cryogenics and superconducting technology simultaneously, e.g., hydrogen-powered aircraft. Given the sensitivity of the reliable and continuous performance of HTS cables, any failures, caused by faults, could be catastrophic, if they are not designed appropriately. Thus, fault analysis of superconducting cables is crucial for ensuring their safety, reliability, and stability, and also for characterising the behaviour of HTS cables under fault currents at the design stage. Many investigations have been conducted on the fault characterisation and analysis of HTS cables in the last few years. This paper aims to provide a topical review on all of these conducted studies, and will discuss the current challenges of HTS cables and after that current developments of fault behaviour of HTS cables will be presented, and then we will discuss the future trends and future challenges of superconducting cables regarding their fault performance.

The second-generation high-temperature superconducting tapes (2G-HTS) such as the REBCO coated conductors are known for their strong mechanical properties and high current carrying capacity with low ac losses compared with first-generation HTS tapes as well as low-temperature superconductors. Therefore, they seem to be good candidates to assemble coils for superconducting rotating electric machines (SuREMs) . In this article, to investigate the influence of a soft magnetic composite (SMC) material on the dc and ac HTS coil performances at cryogenic temperatures, GdBCO- and YBCO-based commercial tapes from different manufactures were used to assemble ten HTS coils in double-pancake configuration. These tapes were wound using two different core structures, i.e., fixed and movable cores, having the same circular shape but different diameters as well as materials, i.e., fiberglass and SMC . Critical currents and ac transport current losses of these coils were measured using the electrical method. To evaluate the parallel and perpendicular components of the profile of magnetic flux density for each assembled HTS coil, a finite element model has been developed using Maxwell 2D. Eventually, the performance of different coils for SuREM application was discussed.

A high-temperature superconducting (HTS) axial flux permanent magnet (AFPM) machine was designed, using superconducting bulks over the rotor surface and rare-earth magnets in the middle of the stator teeth. Because of diamagnetic behavior of the HTS bulks and zero field cooling, leakage flux significantly reduces in the proposed machine compared to the existing machine with mounting rare-earth magnets. Three-dimensional finite element (FE) modelling was used to validate the design performance. The magnetic flux distribution, induced electromotive force (EMF), inductance, PM flux, losses, total harmonic distribution and cogging torque are computed and compared in two structures. The results show that the proposed machine structure is more efficient than the existing one.

It is of great industrial interest and academic importance to investigate current harmonics impacts on AC losses of superconductors, especially in large-scale power devices. However, only effect of amplitude of in-phase current harmonics on AC loss has been studied in the works of literature. We numerically characterized nonsinusoidal AC loss of superconducting tape carrying harmonic currents with orders below 20th versus phase angles. A drastic AC loss variation was found when phase angle was considered for harmonic components. We observed that different harmonic orders show different AC loss profile versus phase angle.

Large scale resistive superconducting fault current limiters (SFCLs) have attracted great interest in electric power systems and aviation applications due to their compactness, lightweight, automatic fault current limiting, and fast recovery characteristics. Noninductive coil wound with stacked conductors in parallel connection is commonly used to achieve high current rating for SFCL. It is of great significance and engineering value to minimize ac losses in the noninductive coil by optimizing the configuration of the stacked conductors in order to reduce the thermal load for the cooling system. In this article, multiple possible configurations of noninductive stacks where each turn is composed of one, two, and three conductors, respectively, were proposed. Numerical models were developed to investigate the effect of noninductive stack configuration on ac loss. Eight-turn noninductive solenoidal coils wound with the noninductive stacks mentioned in the above were also simulated. It is concluded that the configuration of the noninductive stack significantly affects the perpendicular magnetic field distribution in the end edges of the stack. Single-layer configurations have limited magnetic field cancellation effect. The stack configuration with low ac loss and simple structure was suggested.

Application of high-temperature superconducting devices become promising in power networks, and transportation, including ship, train, and electric aircraft propulsion systems, with the advantages of light weight, compact size, and high efficiency, compared to conventional devices. In reality, electric networks-either in grid or transportation propulsion system-are polluted with harmonics due to the widespread use of power electronic devices and nonlinear loads. It is essential to explore the dependency of harmonic ac losses of different coil configurations carrying nonsinusoidal current. We modeled and compared harmonic ac loss behaviors in three coil configurations, single pancake coil (SPC), double pancake coil (DPC), and solenoid coil (SNC), where SPC and SNC are wound by identical wire length and DPC has twice conductor number compared to SPC. The research work has been carried out by means of H-formulation finite element method in a 2-D axisymmetric modeling environment of COMSOL Multiphysics. We explored and reported ac losses in these three coil structures carrying nonsinusoidal current with the third and the fifth harmonic orders, respectively, under different total harmonic distortion (THD) and fundamental current levels. It has been concluded that ac loss in these coils first decreases with the increase of the third harmonic content, when THD of the third harmonic 0.2. AC loss in coils monotonically increases with the increase of the fifth harmonic, drastically. We found that ac loss in SPC carrying the third harmonic and the fifth harmonic at different THD are more than 3.8 times of that in DPC; ac loss in SPC carrying either third or fifth harmonics at different THD are around 4.5 times of that in SNC.

Nowadays, the operation of the smart distribution system (SDS) is more complicated with the penetration of electric vehicles (EVs), due to EVs’ uncertainties as well as the capability of vehicle-to-grid (V2G). On the other hand, distribution transformers (DTs) which have to meet the demand of EVs are one of the essential components of SDS; indeed, their failure can lead to irreparable damage. The cause of most of these failures is overloading and high ambient temperature. The overloading increases the temperature of the various parts of the DTs, especially hot spot temperature (HST). Increasing this temperature reduces the nominal life of the DTs. With a high number of EVs in the future, and as a consequence high energy demand which has not been taken into account in proper operating program, it could lead to the overloading of DTs. So, in this paper, the loss of life (LOL) of a DT that feeds the residential loads and an EV parking lot (EV PL) is investigated. The maximization of the profit of the distribution system operator (DSO) is considered in two different parts i.e. with/without the appropriate operation coefficient (OC) of DT. Also, two different scenarios are applied i.e. charging mode (CM) of EVs and charging/discharging mode (CDM) of EVs. The results show that if the OC is not properly considered, the LOL of the transformers will be significantly high, implying a higher total ownership cost.

High-temperature superconducting (HTS) technology is the most promising, advanced, and beneficial technological developments of the last two decades in terms of fabricating more efficient, compact, and reliable electrical power apparatus. The second-generation HTS wires are now quite competitive with traditional conductors from the cost point of view. In addition, they are of high interest in electrical machine manufacturing due to their unique merits such as high current density, high magnetic field, and low loss. The most significant issue for any superconducting devices which work with alternating current or magnetic field is the AC loss of the HTS tapes. Since HTS tapes are always exposed to an external magnetic field in electrical machine applications, it is vital to consider the effect of this external field on their AC magnetizing (ACMG) loss. It is well-known that external magnetic field decreases the current carrying capability of the wire. In real life, critical current density of HTS tapes is dependent to magnetic field but this dependency sometime was not considered in modeling stage in order to make it faster and simple. In this paper, the electromagnetic properties of HTS tapes for use in superconducting electric machines have been investigated with a particular focus on the ACMG loss of YBCO tapes. For this purpose, a two-dimensional finite element model has been implemented based on the H formulation in order to study the effect of dependency of critical current density to magnetic field on the variation of ACMG loss. The modeling results will be helpful for electrical machine designers to have a better understanding about this effect and have a more accurate estimate of ACMG loss in design stage.

In recent years, there are fast-increasing concerns on the utilizations of superconducting rotating electrical machines in different application areas, such as ship propulsion systems, aircraft drivers, and wind turbine generators, since these machines exhibit the merits of high current density, compact design, high power density, light weight, high torque density as well as high efficiency. One of the main limitations in front of the vast use of superconducting tapes in the fabrication of electrical machineries is AC magnetizing loss when tapes are exposed to an external magnetic field, which can decrease the critical current density of wires, as well. In the literature, most of the research works have been done on calculation of the AC magnetizing loss under a pure external magnetic field, while in reality, magnetic flux lines in AC electrical machines are usually distorted with harmonics because of different reasons such as distorted leakage flux, distributed coils of a winding in several slots, cogging fields, mechanical faults, etc. Since these distorted fields contain harmonics, then in this paper, the AC magnetizing loss of superconducting tapes has been electromagnetically modeled and calculated when they are subjected to nonsinusoidally distorted external magnetic fields. The magnetic field dependency of critical current density has been considered in a proposed finite element model. The results have shown that the AC magnetizing loss increases significantly under a distorted applied field compared with a sinusoidal one. In addition, the loss increase depends on the harmonic content which would increases drastically with total harmonic distortion of the applied magnetic field.

The transient behavior of high temperature superconducting (HTS) cables could significantly depends on fault parameters. This paper investigates impact of fault resistance, fault type, and fault duration time on the transient behavior of a 22.9 kV HTS AC cable. To accomplish this, an equivalent circuit model (ECM) is established to model transient and steady state behaviors of understudied cable, while recovery and twisting effects are also considered. Some simulations were conducted using MATLAB/SIMULINK as case studies to analyze the impact of the fault parameters on the transients of HTS cable. The results were shown that fault and grid parameters drastically change the electromagnetic and thermal behaviors of cable, namely, maximum fault current, maximum temperature, and induced Lorentz force. An increase in the fault resistance could significantly reduce the temperature increase and applied Lorentz force. On the other hand, type of fault changes the maximum induced Lorentz force on tapes and change it from kPa to MPa. Also, the effect of fault duration is studied which shows that a drastic increase in the fault time leads to burnout of tapes.

One of the most promising applications for high temperature superconducting (HTS) material is magnet. HTS magnet is considered to be used in a wide range of applications including MRI, particle accelerator, electrical machine, and etc. HTS rotating machines are mainly utilized for cryo-electrification, i.e. application of superconductivity for modern electrification. One of the main aspects of cryo-electrification is electric aircraft application which is recently enabled by continuous progress in design development of superconducting magnets and HTS machines. This paper discusses the challenges facing a newly developed magnet type, i.e. HTS ring magnet, that being considered in superconducting rotating machine in future electric aircrafts. HTS ring magnet is compact, easy to develop, fault tolerant, and light in weight, and it recently reached to a high level of magnetic field.

There are two main obstacles in front of the development of high temperature superconducting (HTS) technology for electric power network applications; tape price and cooling cost. In order to reduce cooling cost, it is vital to evaluate AC transport current loss of the tapes precisely and then reduce it by some design innovative approaches. In addition, AC transport current loss in HTS material is a critical design variable for large-scale power network applications such as HTS transformers, superconducting fault current limiters, and power cables, since they are continuously carrying the network/load current during their operating life. In existing power networks, harmonic production sources are commonly used and thus, currents are distorted. Therefore, the effect of nonsinusoidal current on the critical apparatus in the network such as transformer must be studied. In this paper, AC transport current loss of a single-turn 2G YBCO HTS coil was modeled and numerically calculated under nonsinusoidal transport current using finite element method. Furthermore, influence of dependency of critical current density to magnetic field on the AC transport current loss of HTS coil when carries distorted currents was considered. It was observed that nonsinusoidal current causes excessive losses in HTS coil. On the other hand, a case study on an HTS transformer supplying non-linear load was considered to study the loss increment as well as heat load change. It was observed that current harmonics increases the AC loss, and heat load of transformer and decreases the efficiency, consequently.

Various kinds of winding arrangements can be used to enable fault current limiters (FCL) to tolerate higher forces without resulting in a substantial increase in construction and fabrication costs. In this paper, a distributed winding arrangement is investigated in terms of its effects on the short-circuit forces in a threephase FCL. The force magnitudes of the AC supplied windings are calculated by employing a finite elementbased model in the time stepping procedure. The leakage flux and radial and axial force magnitudes obtained from the simulation are compared to those obtained from a conventional winding arrangement. The comparison shows that the distributed winding arrangement significantly reduces the radial and, especially, the axial force magnitudes.

The high axial and radial forces caused by short circuits can be very detrimental to high-temperature superconductor (HTS) windings of HTS transformers. Axial forces above the HTS winding critical value cause irreversible effects on the critical current reduction of an HTS tape. Such forces can disrupt the normal performance of HTS transformers and lead to quench phenomenon and insulation breakdown. Accordingly, any optimization in the design of HTS transformers that decreases the leakage flux and electromagnetic forces is very significant. This paper presents a novel method for reduction of leakage flux and thereby electromagnetic force in the windings of an HTS power transformer. First, concentric primary and secondary windings are subdivided into certain number of segments. In the next step, the proposed method, which is based on selecting the optimum distributive ratios for the created subwindings, is applied to the windings. In order to verify the effectiveness of the proposed method, an advanced finite-element method has been used. The method uses accurate and nonlinear $E{-}J$ power law for defining the superconductivity characteristic. The results showed the efficiency of the applied method to mitigate the radial and axial leakage flux and thereby electromagnetic forces in the windings of the HTS transformer.

High-temperature superconducting (HTS) transformer windings operate subcooled at atmospheric pressure to temperatures as low as 65 K, with minimal power dissipation from AC loss in normal operation. During short circuits, HTS transformers are subjected to transient heating by currents as large as 10 times the rated current for durations of up to 2 s. After isolating the fault, HTS transformers are required to cool back down to their base temperature while carrying the operating current. HTS transformer conductors are insulated, typically with wrapped self-adhesive polyimide tape, and windings consist of close-packed conductors wound on composite formers. In this paper, the heat transfer, transient thermal response, and recovery performance of brass-laminated coated conductor HTS wire as well as metallic conductors in liquid nitrogen (LN2) were measured at a range of temperatures from 77 K to 64 K and pressures from atmospheric to 0.14 bar in heating and cooling situations. Measurements were made on bare tapes, and on tapes wrapped with polyimide insulation tape and aramid paper as well as polymer-coated tapes with a range of coating thicknesses. Heat transfer from tapes mounted with one face in contact with a glass-epoxy composite cylindrical former was measured for comparison with free-standing tapes. Using conductors with solid polymer coatings of optimized thickness immersed in subcooled LN2 results in the highest heat transfer and fast recovery following heating to 300 K by a high current pulse. Compared to a bare tape in LN2 at ambient pressure at 77 K, the heat transfer in a coated tape in 65 K subcooled LN2 can be very significantly enhanced by up to a factor of 15, and recovery can be seven times faster.

In recent years, using high-temperature superconductor (HTS) transformers in transportation and electrical power systems has attracted much interest. The major advantages of HTS transformers compared with conventional ones are much smaller size and volume and lighter weight in confined spaces of urban areas or transportation devices. One of the most critical parameters to design, fabricate, and commercialize HTS transformers is hysteresis loss in HTS tapes. Using numerical methods, the accurate value of hysteresis loss and efficiency can be calculated or estimated in HTS transformers. In this paper, two innovative techniques to reduce the leakage flux and thereby hysteresis loss in HTS transformers have been proposed. In the first technique, the concentric windings of HTS transformer are apportioned into a certain number of sub-windings. In the second one, with optimizing the distributive ratios of sub-windings, the windings become unsymmetrical. In order to demonstrate the effectiveness of proposed techniques, an accurate and advanced numerical method based on finite element analysis has been used to design four symmetrical and unsymmetrical primary (P)-secondary (S)-P-S-P and P-S-P-S-P-S-P winding schemes. The simulation results prove the effectiveness of both techniques in reducing the radial and axial leakage flux magnitudes and thereby hysteresis loss in HTS windings.

The Permanent Magnet Brushless DC (PMBLDC) motors have been used in modern industrial factories, hazardous chemical process, modern medical devices, and especially in advanced military devices such as army drones. By considering their sensitive role in the industrial and military applications, their optimal design has a real concern. This paper proposes a method for optimal eco-design of a PMBLDC motor using improved tabu search optimization. The objective function is based on losses, volume and cost. Electrical and mechanical requirements and other limitations are combined into constraints of problem. Also, finite element analysis has been used for verifications in magnetic mode.

Many electrical events can be easily damage electrical equipments in power systems. Such events or faults can be easily stopped at incipient steps but because of weakness of protecting systems they grow and extend, and consequently impose so many problems and cost to utilities. Power transformers are one of the vital equipments in electrical networks and industries, although many protecting systems have been implemented to prevent dangerous electrical faults, but most of them suffer many problems, such as; time wasting, computational burden, and low speed in response. In addition, whenever patterns of fault signals are similar, their discrimination from each other is so hard. Magnetizing inrush current, internal fault, CT saturation and over excitation are common electrical faults in power transformers so that most of the time are difficult to be separated. In this paper all considerations for designing perfect protecting system for power transformers are considered. Using intelligent approach, Artificial Neural Network (ANN) based method is designed. Indeed, proposed protecting system includes two major sections. In the first section, using Bayesian Classifier (BC) which works based on Bayesian rules and uses knowledge of training data directly; internal fault is detected and is discriminated from three other mentioned faults and normal condition. If the event is not internal fault, second condition of this intelligent system makes a decision. In this section, ANN trained by swarm based algorithms, namely; Improved Gravitational Search Algorithm (IGSA) or Particle Swarm Optimization (PSO) is used to discriminate magnetizing inrush current, current transformer (CT) saturation and over excitation. Obtained results show that proposed system can easily and precisely follow the electrical faults in power transformer and detect them at incipient steps. Such quick and accurate response helps to save so much energy, financial cost and time.

Transformers are basically designed to operate under nominal voltage, rated frequency and also, pure sinusoidal load current. In recent decade, change in the type of loads and increasing use of power electronic devices with their nonsinusoidal current waveform has distorted the system voltage waveform as well. The losses of transformers include load and no-load losses. No-load loss continuously led to loss of energy in transformers that are connected to the network in all 24 h. With respect to high significance of energy and undesirable impacts of losses on the aging of transformers, the no-load loss is considered as a critical factor. Nowadays, it is necessary to apply a suitable method for calculation of no-load loss in presence of the voltage harmonics and over-excite conditions, especially for distribution transformers, as a result of harmonic increase in the voltage and current in the network and particular applications. In this paper, Finite Element Method (FEM) has been used to simulate nonsinusoidal voltage effects on no-load loss of transformers. Such simulation enables the software to simulate and analyze different electromagnetic parameters such as flux lines, flux density, losses, and etc under different input sources and with high accuracy. In addition, effect of nonsinusoidal voltages on no-load loss has been investigated by a typical experimental transformer using several practical tests.

Voltage and current distortions caused by nonlinear characteristic of electronic and power electronic devices may cause a large number of problems for electrical equipments such as, mal-operation, additional losses, heat and excessive insulating stresses. Transformers are the most important equipments in power and distribution networks. So, their reliable operation is very critical for utility companies. In this paper, the effects of current distortions caused by electronic devices on the losses of a transformer have been evaluated using ‘finite element method’. Also, the effects of high frequency components of current harmonics on the flux distribution into the transformer's core are investigated. Key words: Distortion, distribution transformers, electronic devices, electronic phase control, finite element method, high frequency flux lines.