Analysis of the Green Power Transition on Optimal Power Transformer Designs

Orosz, Tamás; Sőrés, Péter; Raisz, Dávid; Tamus, Zoltán Ádám

doi:10.3311/ppee.8583

Cited by 20 publications

(15 citation statements)

References 9 publications

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“…The above mentioned four optimization methods have been compared regarding a three-phase, 80 MVA power transformer. For this comparison two different sets of capitalisation factors have been selected (k 1 , k 2 ) from [28]. Thereforethe value of the no-load loss capitalization is k 1 = 7000, the value of the load loss capitalization factor in €/kW k 2 = 1000 €/kW.…”

Section: Test Case Transformer Specificationmentioning

confidence: 99%

Performance Comparison of Multi Design Method and Meta-Heuristic Methods for Optimal Preliminary Design of Core-Form Power Transformers

Orosz

Borbély

Tamus

2017

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

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Large power transformers are regarded as crucial and expensive assets in power systems. Due to the competing global market, to make a good and competing power transformer design, a non-linear optimization problem should be solved in a very short time in the preliminary design stage. The paper shows and compares the performance of four different methods to solve this problem for three phase core type power transformers. The first algorithm is a novel meta-heuristic technique which combines the geometric programming with the method of branch and bound. Then this conventional multi design method is solved by a simple iterative technique and two novel evolutionary algorithms to enhance the convergence speed. One of these algorithms is the particle swarm optimization technique which is used by many other researchers and the grey wolf optimization algorithm which is a new method in this optimization sub-problem. An example design on an 80 MVA, three phase core type power transformer using these four methods is presented and its performances are analyzed. The results demonstrate that the grey wolf optimization is a good alternative for this optimization problem.

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Section: Test Case Transformer Specificationmentioning

confidence: 99%

Performance Comparison of Multi Design Method and Meta-Heuristic Methods for Optimal Preliminary Design of Core-Form Power Transformers

Orosz

Borbély

Tamus

2017

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

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“…It is important to consider not only the technical feasibility, but the economic aspects, as well. Generally, the total cost of ownership (TOC) is used as a goal function [4] to consider the lifetime costs of the transformer [2,[4][5][6][7][8].…”

Section: Introductionmentioning

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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“…Various diagnostic systems exist for transformers [9][10][11]. The developed diagnostic methods for transformers are divided into off-line and on-line methods [12,13].…”

Section: Introductionmentioning

confidence: 99%

Optimal Techno-economic Sequence-based Set of Diagnostic Tests for Distribution Transformers Using Genetic Algorithm

Hashemi‐Dezaki

Rubanenko

Hryshchuk

2020

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

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The diagnostic measurement and tests of transformers are essential. Also, the costs of diagnostic tests are considerable. Hence, proposing a method to determine an economic-technical sequence-bases set of diagnostic tests for transformers is useful and interesting. In this paper, a new method is proposed to determine the optimal sequence-based set of diagnostic tests for distribution transformers. A new objective function based on the branch and bound concept is developed in this paper. The proposed optimization problem is solved by using the Genetic Algorithm (GA). The statistical data regarding the experimental diagnostic tests for more than 20 distribution transformers of South-West Power System Company (Pivdenno-Zakhidna Power System) located in Ukraine have been used. The usage of the actual statistical data of distribution transformers is one of the most important contributions of this paper. The comparison of the obtained optimum test results and those of a typical conventional non-optimum sequence of diagnostic tests illustrate the advantages of the proposed method. By applying the proposed method, it is achievable to perform the comprehensive diagnostic tests with the minimum required costs.

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Analysis of the Green Power Transition on Optimal Power Transformer Designs

Abstract: The main intent of the power transformer design optimization

Cited by 20 publications

References 9 publications

Performance Comparison of Multi Design Method and Meta-Heuristic Methods for Optimal Preliminary Design of Core-Form Power Transformers

Performance Comparison of Multi Design Method and Meta-Heuristic Methods for Optimal Preliminary Design of Core-Form Power Transformers

FEM Based Preliminary Design Optimization in Case of Large Power Transformers

Optimal Techno-economic Sequence-based Set of Diagnostic Tests for Distribution Transformers Using Genetic Algorithm

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