Core-form transformer design optimization with branch and bound search and geometric programming

Orosz, Tamás; Sleisz, Ádám; Vajda, Igor

doi:10.1109/rtucon.2014.6998194

Cited by 14 publications

(16 citation statements)

References 7 publications

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“…He rejected to use the manufacturing cost as the objective function, instead of this he was proposed to use the sum of the manufacturing and the operating costs as the objective of the optimization. This phenomenon is similar to the modern lifetime cost optimization approaches [1,91,[103][104][105][106][107] (Fig. 5).…”

Section: Analytical Cost Optimization Methodssupporting

confidence: 74%

“…Following this axiom, the application of larger main gap increases the cost of the active part of an electrical machine. Due to the non-linearity of the electrical machine design problem this design principle does not corresponds with the practice, where the cost optimal transformers, autotransforemrs have larger main gap than the required minimum [5,8,13,14,104]. Csikos has already confuted another old design rule [103], which states that if the transformer designed for maximal efficiency it has as same load as no-load losses.…”

Section: Analytical Cost Optimization Methodsmentioning

confidence: 99%

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Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Orosz

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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Transformer design is a challenging engineering task, where the different physical fields have to be harmonized together to fulfill the implied specifications. Due to the difficulty of this task, it can be separated into several subproblems. The first subproblem, in the pre-concept phase, during the transformer design is the calculation of the cost optimal key-design parameters, where not only the technical but also the economical parameters have to be considered, as well. This subproblem belongs to the most general branch of the non-linear mathematical optimization problems. This paper presents the main directions of the evolution and trends in the power transformer design. Main directions of the considered research and the future trends in the field of preliminary design transformer optimization methods are summarized.

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Section: Analytical Cost Optimization Methodssupporting

confidence: 74%

Section: Analytical Cost Optimization Methodsmentioning

confidence: 99%

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Orosz

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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“…These practical formulas are the results of measurements, which are made by an Epstein-apparatus and they are take the hysteresis and eddy losses into account. The applied loss function is fitted to the applied electrical steel data (M1H [45]) and approximated by a polynomial expression [9,14,27,46]:…”

Section: Core Mass and No-load Loss Calculationmentioning

confidence: 99%

FEM Based Preliminary Design Optimization in Case of Large Power Transformers

2020

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Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

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“…To formulate a problem in GP format, the equality constraints shall be formulated in monomial form, and the inequalities in a special posynomial form [26]. The previous articles of the authors [24,25] have shown that the short circuit impedance cannot be formulated in either monomial nor in posynomial format properly. A solution for the problem has be shown by the combination of this method with a branch and bound search [25].…”

Section: The Geometric Programming Based Meta-heuristic Algorithmmentioning

confidence: 99%

“…Therefore in the last decades, a wide range of mathematical optimisation methods have been implemented for this design optimisation problem, such as Monte Carlo simulation [18], artificial intelligence techniques and neural networks [19], evolutionary and genetic algorithms [13][14][15][16][17][18], and geometric programming (GP) [1,20,24,25]. The importance of GP is based on the recent developments in the solution methods, which can solve even large-scale GPs extremely efficiently and accurately [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Impact of the Cooling Equipment on the Key Design Parameters of a Core–Form Power Transformer

Orosz

Tamus

2016

Journal of Electrical Engineering

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The first step in the transformer design process is to find the active part's key design parameters. This is a non-linear mathematical optimisation task, which becomes more complex if the economic conditions are considered by the capitalisation of the losses. Geometric programming combined with the method of branch and bound can be an effective and accurate tool for this task even in the case of core-form power transformers, when formulating the short-circuit impedance in the required form is problematic. Most of the preliminary design methods consider only the active part of the transformer and the capitalised costs in order to determine the optimal key design parameters. In this paper, an extension of this meta-heuristic transformer optimisation model, which takes the cost of the insulating oil and the cooling equipment into consideration, is presented. Moreover, the impact of the new variables on the optimal key design parameters of a transformer design is examined and compared with the previous algorithm in two different economic scenarios. Significant difference can be found between the optimal set of key-design parameters if these new factors are considered.

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Core-form transformer design optimization with branch and bound search and geometric programming

Cited by 14 publications

References 7 publications

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

Evolution and Modern Approaches of the Power Transformer Cost Optimization Methods

FEM Based Preliminary Design Optimization in Case of Large Power Transformers

Impact of the Cooling Equipment on the Key Design Parameters of a Core–Form Power Transformer

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