Author:
Penabad Durán Patricia,Di Barba Paolo,Lopez-Fernandez Xose,Turowski Janusz
Abstract
Purpose
– The purpose of this paper is to describe a parameter identification method based on multiobjective (MO) deterministic and non-deterministic optimization algorithms to compute the temperature distribution on transformer tank covers.
Design/methodology/approach
– The strategy for implementing the parameter identification process consists of three main steps. The first step is to define the most appropriate objective function and the identification problem is solved for the chosen parameters using single-objective (SO) optimization algorithms. Then sensitivity to measurement error of the computational model is assessed and finally it is included as an additional objective function, making the identification problem a MO one.
Findings
– Computations with identified/optimal parameters yield accurate results for a wide range of current values and different conductor arrangements. From the numerical solution of the temperature field, decisions on dimensions and materials can be taken to avoid overheating on transformer covers.
Research limitations/implications
– The accuracy of the model depends on its parameters, such as heat exchange coefficients and material properties, which are difficult to determine from formulae or from the literature. Thus the goal of the presented technique is to achieve the best possible agreement between measured and numerically calculated temperature values.
Originality/value
– Differing from previous works found in the literature, sensitivity to measurement error is considered in the parameter identification technique as an additional objective function. Thus, solutions less sensitive to measurement errors at the expenses of a degradation in accuracy are identified by means of MO optimization algorithms.
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computational Theory and Mathematics,Computer Science Applications
Reference18 articles.
1. Cranganu-Cretu, B.
and
Schneider, M.
(2009), “Coupled electromagnetic-thermal analysis for ABB power transformers”, paper presented at International Colloquium Transformer Research and Asset Management, Cavtat, November 12-14.
2. Deb, K.
,
Pratap, A.
,
Agarwal, S.
and
Meyarivan, T.
(2002), “A fast and elitist multiobjective genetic algorithm: NSGA-II”,
IEEE Transactions on Evolutionary Computation
, Vol. 6 No. 2, pp. 182-197.
3. Di Barba, P.
(2010),
Multiobjective Shape Design in Electricity and Magnetism
, Springer.
4. Di Barba, P.
,
Mognaschi, M. E.
,
Savini, A.
and
Turowski, J.
(2005), “Cost-effective optimal design of screens in power transformers”, Computer Engineering in Applied Electromagnetism (Proceedings of the 11th International Symposium on Electromagnetic Fields in Electrical Engineering – ISEF 2003), Springer, pp. 41-45.
5. Flux3D FEM
(2014), “Software Package v.11.1.1”, available at: www.cedrat.com/en/software/flux.html (accessed August 13, 2014).
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献