Optimization of Distributive Ratios of Apportioned Winding Configuration in HTS Power Transformers for Hysteresis Loss and Leakage Flux Reduction

Ghabeli, Asef; Yazdani-Asrami, Mohammad; Besmi, Mohammad Reza; Gholamian, S. Asghar

doi:10.1007/s10948-015-3165-8

Cited by 17 publications

(8 citation statements)

References 31 publications

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“…The ability to continuously overload operation without degradation of insulation due to thermal stresses is another advantage of HTS transformers. Fault tolerant HTS transformers operate not only to regulate the voltage level but also to limit the fault current [30][31][32][33][34][35].…”

Section: Applications Of Scs and The Challengesmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

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More than a century after the discovery of superconductors (SCs), numerous studies have been accomplished to take the advantage of SCs in physics, power engineering, quantum computing, electronics, communications, aviation, health care, 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 on 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 full commercialization of SCs and their applications. AI approaches are capable of providing fast, efficient, and accurate solutions for the technical, manufacturing, and economic problems with a high level of complexity and nonlinearity in the field of superconductivity. In this paper, 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. The topical review are presented in three main categories, AI for large-scale superconducting applications, AI for superconducting materials, and AI for physics of superconductors. In addition, the challenges to apply AI techniques to the superconductivity and its applications are given. Eventually, future trends on how to integrate AI techniques with superconductivity towards the commercialization are discussed.

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Section: Applications Of Scs and The Challengesmentioning

confidence: 99%

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Yazdani-Asrami

Sadeghi

Song

et al. 2022

Supercond. Sci. Technol.

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“…Most of the Finite Element Methods (FEM) used for simulating superconductors including tapes, coils, and stacks (such as methods utilizing commercial software) employ boundary conditions at the external surface of the air domain. The air domain should be large enough (around 10 times bigger than the dimension of superconducting object) in order to obtain a precise solution, and hence it must be meshed [59], [60]. This adds a significant number of mesh elements to the solution and thus significant extra computing time.…”

Section: Introductionmentioning

confidence: 99%

Modeling of airgap influence on DC voltage generation in a dynamo-type flux pump

Ghabeli

Pardo

2020

Supercond. Sci. Technol.

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“…As for Fujikura tape, three parameters, k = 0.71, B0 = 100 mT and = 0.23 are characteristics associated with magnetic field dependence of the materials [3].…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, it is very important for the design and industrialization of superconducting transformer to accurately Xu Liao, Jin Fang, Xin Zhao, Song Yang, Yueming Sun, Yue Wu are with calculate the AC loss of HTS transformer. Over the past decade, research groups have been designing, manufacturing and testing HTS transformers used in various fields [1][2][3][4]. Since 2018, Beijing jiaotong University has been leading a six-party cooperation project to develop a 6.5 MVA HTS traction transformer for high-speed trains.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Electromagnetic Characteristics of 6.5 MVA/25 kV HTS Traction Transformer Using T–A Formulation

Liao

Fang

Zhao

et al. 2023

IEEE Trans. Appl. Supercond.

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Low AC loss of the winding of high-capacity high temperature superconducting (HTS) traction transformer is a very important link to introduce large capacity traction transformer into commercialization. A new winding structure is proposed for the transformer. The HV windings are made of double pancake coils (DPCs), which are wound by 4.8 mm-wide tapes, and the LV windings, which are wound by 12 mm-wide tapes, are solenoid coils. The electromagnetic characteristics of the new winding structure of the traction transformer are analyzed by H-formulation homogenization method and T-A formulation homogenization method respectively. Significant HTS tape cost reduction could be achieved without compromising AC loss by using hybrid windings into the new winding structure. We report that the H-formulation homogenization model and T-A formulation homogenization model are used to calculate the AC loss of the new winding structure with flux diverters (FDs) at the end. The results meet the design requirements of less than 2 kW, which shows the feasibility of the new winding structure. Due to the good convergence of H-formulation and poor convergence of T-A formulation under the homogenization model of the transformer, no one has used T-A formulation to calculate the electromagnetic characteristics of the transformer before. Due to the simplicity of T-A formulation applied to large-scale superconducting system, a new form of mesh generation is proposed to improve the convergence and accuracy of T-A formulation homogenization model calculation of the transformer in this paper. This paper verifies the correctness of the calculation of HTS transformer by T-A formulation, and provides a reference for the application of T-A formulation in more superconducting fields.

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Optimization of Distributive Ratios of Apportioned Winding Configuration in HTS Power Transformers for Hysteresis Loss and Leakage Flux Reduction

Cited by 17 publications

References 31 publications

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Modeling of airgap influence on DC voltage generation in a dynamo-type flux pump

Analysis of Electromagnetic Characteristics of 6.5 MVA/25 kV HTS Traction Transformer Using T–A Formulation

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