Transformer Design Optimization Research Articles

Harmony Search Approach Based on Ricker Map for Multi-Objective Transformer Design Optimization

Harmony search (HS) algorithm is an evolutionary optimization algorithm developed in an analogy with an improvisation process where musicians try to polish their pitches to obtain a better harmony. In this paper, a modified HS (MHS) algorithm is adapted to multi-objective optimization using external archiving, ranking with crowding distance, and control parameters tuning based on Ricker map to solve a transformer design optimization (TDO) problem with two competing objectives. Simulations applied to a TDO problem demonstrate the effectiveness of the proposed multi-objective MHS algorithm. Results indicate that, compared with other multi-objective HS algorithm, in terms of output quality, the proposed MHS is able to find competitive solutions with a good tradeoff between the design objectives.

Analysis of the Green Power Transition on Optimal Power Transformer Designs

The main intent of the power transformer design optimization in the tendering stage is to find those mechanical and electrical parameters, which minimize the machines’ total cost of the ownership by reducing the different power losses and the manufacturing costs. To find the optimal transformer design parameters and make them harmonize with the economic constraints is a labour intensive task, because these quantities are linked with complex trade-off and physical functions. The capitalization of the load and no-load losses facilitate this process. The focus of this paper is to examine the sensitivity of the design parameters from the capitalization factors. Three different scenarios are presented and analysed in this paper, where the transformers are connected to various stochastic or schedulable green power generation resources. This paper presents the optimal transformer design’s dependency from the various scenarios of different green power generation resources.

Optimal Design of High Frequency Transformer for 150W Class Module-Integrated Converter

Recently, the module-integrated converter has shown an interest in the photovoltaic generation system. In this system, the high frequency transformer should be compact and efficient. The proposed method is based on the correlation characteristic between the copper and core loss to minimize the loss of transformer. By sizing an effective cross-sectional area and window area of core, the amount of loss is minimized. This paper presents the design and analysis of high frequency transformer by using the 3D finite element model coupled with DC-DC converter circuit for more accurate analysis by considering the nonlinear voltage and current waveforms in converter circuit. The current waveform in each winding is realized by using the ideal DC voltage source and switching component. And, the thermal analysis is performed to satisfy the electrical and thermal design criteria.

Application of Advanced Numerical Modelling to Analysis of Transformer Operation and Design Optimization

This paper provides examples of application of advanced numerical modelling to analysis of transformer operation and design optimization. Computer simulations are useful tools that help engineers in keeping the balance between the continuous pursuit of reducing the cost of transformers and assuring high quality performance. The presented examples refer to different types of transformers and different problems in their operation. They include analysis of thermal shock test of the dry transformer, analytical, experimental and numerical modeling for improvement of passive cooling in oil-immersed distribution transformers and seismic analyses of power transformers. In each case the numerical modelling approach is presented and the example results are shown. Simulations of thermal shock test indicate large temperature gradients that may have essential influence on mechanical behavior of the dry transformer coil. Further, the higher cooling efficiency of the new concept of passive cooling is validated using mathematical, numerical and experimental models. Finally, the proposed numerical methods of seismic analysis indicates that oil has an influence on structure dynamics and the whole transformer system must be taken into account during vibration analysis.

Modified parameter optimization of distribution transformer design using covariance matrix adaptation evolution strategy

Optimal transformer design (TD) is a complex multi-modal, multi-objective, mixed-variable and non-linear problem. This paper discusses the application of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for distribution TD, minimizing four objectives; purchase cost, total life-time cost, total mass and total loss individually. Two independent variables; voltage per turn and type of magnetic material are proposed to append with the usual TD variables, aiming at cost effective, reduced weight, and energy efficient TD. Three case studies with three sets of TD vectors are implemented on 400KVA, 20/0.4KV transformer to demonstrate the superiority of Modified Design Variables (MDV), in terms of cost savings, material savings, and loss reduction. Simulation results of CMA-ES provide better TD on comparison with conventional transformer design procedure, branch and bound algorithm tailored to a mixed-integer non-linear programming, Self Adaptive Differential Evolution (SaDE), and real coded GA (RGA). Statistical analysis has proven the faster convergence and consistency of CMA-ES. Moreover, NSGA-II is applied for solving multi-objective TD optimization problem with the aim of providing tradeoff between conflicting TD objectives.

Optimal Analysis and Design of Power Electronic Distribution Transformer

This study proposes a new design of Power Electronic distribution Transformer (PET) by using an intelligent program to get an optimum HF operation, which leads to maximum efficiency. This PET has three stages; the input stage consists of three phases, three level PWM rectifier and isolation stage employing three level half bridge convertor connected with high frequency transformer. The output stage has a matrix converter. This new design of PET has the advantage of improving power factor, voltage sags, voltage swell, reactive power compensation, eliminating harmonic and controlling and Protecting its self (PET) with minimum size, compared to the traditional transformer. The software like MATLAB and Artificial Neural Network will be used to analyze and simulate the PET.

Multiobjective Optimization of Transformer Design Using a Chaotic Evolutionary Approach

The design of a transformer must meet minimum requirements of efficiency and regulation, maximizing the power to be transferred per unit of mass or volume, and supports a well defined maximum elevation of temperature. Conflicting objectives lead to the employment of optimization methods in the transformer design. Multiobjective optimization problems (MOPs) consist of several competing and incommensurable objective functions. Recently, as a search and optimization technique inspired by nature, evolutionary algorithms (EAs) have been broadly applied to solve MOPs. Various EAs have been proposed for this purpose, and their usefulness has been demonstrated in several application domains of science and engineering. In this paper, we propose the unrestricted population-size evolutionary multiobjective optimization algorithm (UPS-EMOA) approach combined with chaotic sequences (CMOA). Our approach integrates the merits of both UPS-EMOA and chaotic sequences to improve the efficiency of the optimization procedure. Numerical results of transformer design optimization demonstrate the effectiveness of the proposed CMOA when compared with the UPS-EMOA approach to preserve the diversity of the solutions and find nondominated solutions.

Global Transformer Design Optimization Using Deterministic and Nondeterministic Algorithms

This paper compares the application of two deterministic and three nondeterministic optimization algorithms to global transformer design optimization (TDO). Two deterministic optimization algorithms (mixed-integer nonlinear programming and heuristic algorithm) are compared to three nondeterministic approaches (harmony search, differential evolution, and genetic algorithm). All these algorithms are integrated in design optimization software applied and verified in the manufacturing industry. The comparison yields significant conclusions on the efficiency of the algorithms and the selection of the most suitable one for the TDO problem.

Optimal Transformer Design for Ultraprecise Solid State Modulators

In this paper, a procedure for optimal transformer design with a variable set of constraints for pulse transformers with a pulse range of 3-140 μs is presented. During the optimization procedure, the pulse shape is analyzed in the time domain, ensuring that the pulse constraints, such as rise time and overshoot are met. For accurate prediction of the pulse shape, analytical approaches are proposed to estimate the distributed capacitance and leakage inductance of the transformer. The analytical approach is verified by 2-D-FEM simulations and measurements. The optimization procedure considers pulse, core, winding, demagnetization losses, and losses of the primary switches. First, the procedure is applied to an existing pulse transformer with specifications for SwissFEL. An improvement of 16.6% in conversion efficiency is achieved in comparison with the existing design. In a second step, the procedure is applied to specifications of the compact linear collider, which demands high conversion efficiency. The resulting optimal transformer consists of three cores with five primary turns and requires a tank volume of 0.915 m3. In an optimal configuration, an overall conversion efficiency of 97.7% is achieved for the considered system including pulse losses.

The Ultrasonic Honing of Amplitude Transformer's Optimal Design Based on VB Platform

Based on VB, start from the performance requirements of ultrasonic honing for the amplitude transformer, and derive the amplitude transformer wave equation and boundary conditions. Then, establish a resonance frequency equation, programming iterating the critical size of the Amplitude transformer. To get the optimal solution, verified the results of optimal design by experiment. Experiments show that the optimal design is feasible, fast and accurate, possess of great practical value. It has played a prominent effect for further optimal design and processing applications of ultrasonic honing.

Novel Gamma Differential Evolution Approach for Multiobjective Transformer Design Optimization

The differential evolution (DE) algorithm is a simple but powerful population-based stochastic search technique for solving global optimization problems. DE consists of three main operations: mutation, crossover and selection. The advantages of DE are simple structure, ease of use, speed and robustness. However, to achieve optimal performance with DE, time consuming parameter tuning is essential as its performance is sensitive to the choice of the mutation and crossover values. In this paper, a novel DE algorithm (NDE) based on truncated gamma probability distribution function is proposed for solving multiobjective optimization problems as the design of transformers. Simulations of transformer design optimization (TDO) demonstrate the effectiveness of the proposed optimization algorithm. The simulation results show that, compared with other multiobjective DE algorithm, the proposed NDE is able to find better spread of solutions with better convergence to the Pareto front and preserve the diversity of Pareto solutions more efficiently.

Optimal design of a furnace transformer by intelligent evolutionary methods

This paper presents three intelligent evolutionary optimization techniques to investigate the optimal design parameters of a 3-phase furnace transformer. The transformer rating is derived from the operating conditions of a medium size direct arc furnace. Scatter Search (SS), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques are employed on the developed nonlinear mathematical model of the transformer for constrained optimization minimizing the cost. The design and analysis programs of the furnace transformer are developed using codes written in C++/C language. The optimal design data results validated by an example show the efficacy of the three intelligent techniques. Among the three methods, the optimal results obtained by GA and PSO techniques show the potential for implementing as efficient search techniques for design optimization of furnace transformers.

Optimal Design and Tradeoff Analysis of Planar Transformer in High-Power DC–DC Converters

The trend toward high power density, high operating frequency, and low profile in power converters has exposed a number of limitations in the use of conventional wire-wound magnetic component structures. A planar magnetic is a low-profile transformer or inductor utilizing planar windings, instead of the traditional windings made of Cu wires. In this paper, the most important factors for planar transformer (PT) design including winding loss, core loss, leakage inductance, and stray capacitance have individually been investigated. The tradeoffs among these factors have to be analyzed in order to achieve optimal parameters. Combined with an application, four typical winding arrangements have been compared to illustrate their advantages and disadvantages. An improved interleaving structure with optimal behaviors is proposed, which constructs the top layer paralleling with the bottom layer and then in series with the other turns of the primary, so that a lower magnetomotive force ratio m can be obtained, as well as minimized ac resistance, leakage inductance, and even stray capacitance. A 1.2-kW full-bridge dc-dc converter prototype employing the improved PT structure has been constructed, over 96% efficiency is achieved, and a 2.7% improvement, compared with the noninterleaving structure, is obtained.

Discrete Design Optimization of Small Open Type Dry Transformers

Discrete Design Optimization of Small Open Type Dry Transformers

The Analysis of Leakage Magnetic Field in the Large-Capacity Transformer

With the increase of transformer capacity, local overheating caused by leakage magnetic field affects the normal work and safe problems of transformer. How to reduce the additional loss and eliminate local overheating must be paid full attention to the design and manufacturing process of large transformer. In this paper, the leakage magnetic fields of clamps, clips and tank are analyzed. The distribution of leakage magnetic field in various parts of the transformer is obtained. Results of the analysis according with the engineering practice will be helpful for the optimal design of transformer.

Optimal design of multi-winding transformer using combined FEM, Taguchi and stochastic-deterministic approach

A multi-objective design optimisation for double primary and secondary winding transformers is presented in the study, with the aim to minimise the deviation between the prescribed and designed short-circuit impedance values. The optimisation process involves the exploitation of the results of an efficient and experimentally validated finite element model for leakage field prediction by the Taguchi method. The model is used in conjunction with evolutionary stochastic and deterministic optimisation algorithms in order to derive the optimal winding configuration that meets the technical requirements for the compound multi-winding short-circuit impedance target value.

Discrete Design Optimization of Small Open Type Dry Transformers

Discrete Design Optimization of Small Open Type Dry Transformers

Design Optimization of High-Frequency Power Transformer by Genetic Algorithm and Simulated Annealing

This paper highlights the transformer design optimization problem. The objective of transformer design optimization problem requires minimizing the total mass (or cost) of the core and wire material by satisfying constraints imposed by international standards and transformer user specification. The constraints include appropriate limits on efficiency, voltage regulation, temperature rise, no-load current and winding fill factor. The design optimizations seek a constrained minimum mass (or cost) solution by optimally setting the transformer geometry parameters and require magnetic properties. This paper shows the above design problems can be formulated in genetic algorithm(GA) and simulated annealing (SA) format. The importance of the GA and SA format stems for two main features. First it provides efficient and reliable solution for the design optimization problem with several variables. Second, it guaranteed that the obtained solution is global optimum. This paper includes a demonstration of the application of the GP technique to transformer design. Key word — Optimization, Power Transformer, Genetic Algorithm (GA), Simulated Annealing Technique (SA) DOI: http://dx.doi.org/10.11591/ijece.v1i2.88

Optimization of a 5-kW Telecom Phase-Shift DC–DC Converter With Magnetically Integrated Current Doubler

The development of new converter systems with higher power density and/or efficiency offers many degrees of freedom for the design parameters as a large number of system component values have to be defined, where all of which are interdependent, to some extent, on another. Therefore, an automated optimization procedure, based on comprehensive analytical models and the resulting optimal design parameters, e.g., switching frequency or transformer design, to achieve the most compact and/or efficient design, is presented in this paper. In addition, the design of a volume-optimized 400/46-56-V phase-shift dc-dc converter with a current doubler rectifier and the underlying analytical models are also introduced. The power density of the converter is increased by integrating the output inductors in the transformer's core. A new lossless magnetic snubber circuit is introduced, which damps the intrinsic voltage ringing of the rectifier diodes and feeds the ringing energy to the output. The experimental results prove the analytical models and the design procedure. The 5-kW dc-dc converter prototype has a power density of 147 W/in3 (9 kW/L) and a maximum efficiency of 94.4% at 54-V output voltage and full load.

An Optimal Process for Ultrasonic Amplitude Transformer Design with FEM

The amplitude transformer is one of the most important parts in ultrasonic work system. To amplitude transformer, the resonant frequency and location of flange are two crucial design objectives. For variable cross-section amplitude transformer design, the traditional theory calculation seems to be too verbose and sometime hard to get efficient solution. This paper focuses on using commercial FEM software-ANSYS to achieve an optimal design of amplitude transformer.