Transformer Design and Optimization: A Literature Survey

Dept. of Production Eng. & Manage., Tech. Univ. of Crete, Chania, Greece
IEEE Transactions on Power Delivery (Impact Factor: 1.73). 11/2009; 24(4):1999 - 2024. DOI: 10.1109/TPWRD.2009.2028763
Source: IEEE Xplore


With the fast-paced changing technologies in the power industry, new references addressing new technologies are coming to the market. Based on this fact, there is an urgent need to keep track of international experiences and activities taking place in the field of modern transformer design. The complexity of transformer design demands reliable and rigorous solution methods. A survey of current research reveals the continued interest in application of advanced techniques for transformer design optimization. This paper conducts a literature survey and reveals general backgrounds of research and developments in the field of transformer design and optimization for the past 35 years, based on more than 420 published articles, 50 transformer books, and 65 standards.

Download full-text


Available from: Eleftherios I. Amoiralis,

Click to see the full-text of:

Article: Transformer Design and Optimization: A Literature Survey

0 B

See full-text
  • Source
    • "From the overview of research papers in TD, efforts are focusing on prediction of specific transformer characteristics, techniques adopted for transformer design optimization, transformer post design performance and modeling and recent trends on transformer technology. In a nutshell, TD optimization problem remains an active area [1]. TD optimization can be minimization of no-load loss [2] [3], minimization of load loss [4], maximization of efficiency [5] [6] [7] [8], maximization of rated power [9], minimization of mass [9] or minimization of cost [5,6,10–19], based on the objective functions. "
    [Show abstract] [Hide abstract]
    ABSTRACT: 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 400 KVA, 20/0.4 KV 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.
    International Journal of Electrical Power & Energy Systems 10/2014; 61:208–218. DOI:10.1016/j.ijepes.2014.03.039 · 3.43 Impact Factor
  • Source
    • "Therefore, the objective function is a cost function with many terms, including material costs, labor costs, and overhead costs. These component costs, as well as the constraint functions, must be expressed in terms of a basic set of design variables [1]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper compares the application of two deter-ministic 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 optimiza-tion 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.
    IEEE Transactions on Industrial Electronics 01/2014; 50(1). DOI:10.1109/TIA.2013.2288417 · 6.50 Impact Factor
  • Source
    • "Recently, optimization of coils and cooling ducts in dry-type transformers with the aim to minimize the average and maximum winding temperatures has been carried out [12]. However, although transformer panels play an important role in the cooling system performance and optimization, no specific study on their shape optimization can be encountered in the relevant literature [4]. The present paper introduces novel shape configurations of transformer panels as a part of overall cooling system improvement of oil-immersed ONAN transformers. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Increase of temperature rise and hot spot values affects dramatically transformer aging and life expectancy. The present article investigates several improved designs of ONAN transformer cooling system by means of advanced numerical heat transfer-fluid flow model. Novel tank designs are examined in conjunction with other crucial parameters, as the number and location of the winding cooling ducts, so as to define the best geometry that ensures maximum efficiency of the transformer cooling system, with the aim of expanding transformer lifetime.
    IEEE Transactions on Dielectrics and Electrical Insulation 06/2012; 1900(3). DOI:10.1109/TDEI.2012.6215108 · 1.28 Impact Factor
Show more