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Thermal Response Estimation in Substation Connectors Using Data-Driven ModelsGIACOMETTO, F. , CAPELLI, F. , ROMERAL, L. , RIBA, J.-R. , SALA, E.
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computer simulation, connectors, finite element methods, predictive models, thermal analysis
engineer(8), comput(7), neural(6), jcie(6), indust(6), simulation(5), process(5), finite(5), element(5), time(4)
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About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 25 - 30
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03004
Web of Science Accession Number: 000384750000004
SCOPUS ID: 84991096061
Temperature rise simulations are one of the key steps in the design of high-voltage substation connectors. These simulations help minimizing the number of experimental tests, which are power consuming and expensive. The conventional approach to perform these simulations relies on finite element method (FEM). It is highly desirable to reduce the number of required FEM simulations since they are time-consuming. To this end, this paper presents a data-driven modeling approach to drastically shorten the required simulation time. The data-driven approach estimates the thermal response of substation connectors from the data provided by a reduced number of FEM simulations of different operating conditions, thus allowing extrapolating the thermal response to other operating conditions. In the study, a partitioning method is also applied to enhance the performance of the learning stage of a set of data-driven methods, which are then compared and evaluated in terms of simulation time and accuracy to select the optimal configuration of the data-driven model. Finally, the complete methodology is validated against simulation tests.
|References|||||Cited By «-- Click to see who has cited this paper|
| G. Mazzanti, "The Combination of Electro-thermal Stress, Load Cycling and Thermal Transients and its Effects on the Life of High Voltage ac Cables", IEEE Trans. Diel. Electr. Insul., vol. 16, pp. 1168-1179, 2009, |
[CrossRef] [Web of Science Times Cited 61]
 National electrical Manufacturers Association, "ANSI/NEMA CC 1-2009 Electric Power Connection for Substations Standart", NEMA Communications Department, Arlington, Virginia, 2009
 J. J. A. Wang, E. Lara-Curzio, T. King, J. A. Graziano, and J. K. Chan, "The integrity of ACSR full tension splice connector at higher operation temperature", IEEE Trans. Power Deliv., vol. 23, pp. 1158-1165, 2008,
[CrossRef] [Web of Science Times Cited 10]
 J. Hernandez-Guiteras, J. R. Riba, and L. Romeral, "Redesign process of a 765 kVRMS AC substation connector by means of 3D-FEM simulations", Sim. Model. Pract. Theory, vol. 42, pp. 1-11, 2014,
[CrossRef] [Web of Science Times Cited 12]
 F. Capelli, J. R. Riba, and D. Gonzalez, "Optimization of short-circuit tests based on finite element analysis", in IEEE International Conference on Industrial Technology (ICIT), pp. 1368-1374, 2015,
 S. Jia, J. F. Bard, R. Chacon, and J. Stuber, "Improving performance of dispatch rules for daily scheduling of assembly and test operations", Comput. Indust. Engineer., vol. 90, pp. 86-106, 2015,
[CrossRef] [Web of Science Times Cited 8]
 U. Roy, "An intelligent interface between symbolic and numeric analysis tools required for the development of an integrated CAD system", Comput. Indust. Engineer., vol. 30, pp. 13-26, 1996,
[CrossRef] [Web of Science Times Cited 5]
 F. Tian and M. Voskuijl, "Automated generation of multiphysics simulation models to support multidisciplinary design optimization", Advan. Engineer. Informat., 2005,
[CrossRef] [Web of Science Times Cited 8]
 T. Altan and V. Vazquez, "Numerical Process Simulation for Tool and Process Design in Bulk Metal Forming", CIRP Annals - Manuf.. Technol., vol. 45, pp. 599-615, 1996,
 S. Cho, "A distributed time-driven simulation method for enabling real-time manufacturing shop floor control", Comput. Indust. Engineer., vol. 49, pp. 572-590, 2005,
[CrossRef] [Web of Science Times Cited 14]
 Y. Zhang, Z.-P. Fan, and Y. Liu, "A method based on stochastic dominance degrees for stochastic multiple criteria decision making", Comput. & Indust. Engineer., vol. 58, pp. 544-552, 2010,
[CrossRef] [Web of Science Times Cited 49]
 Z. Lou and H. M. Jin, "A novel dual-field time-domain finite-element domain-decomposition method for computational electromagnetics", IEEE Trans. Antennas Propagat., vol. 54, pp. 1850-1862, 2006,
[CrossRef] [Web of Science Times Cited 41]
 M. Nesme, F. Faure, and Y. Payan, "Hierarchical multi-resolution finite element model for soft body simulation", Biomedical Simulation, Proceedings, vol. 4072, pp. 40-47, 2006,
 U. K. Malte Neumann, S. R. Tiyyagura, W. A. Wall, and E. Ramm, "High Performance Computing on Vector Systems: Computational Efficiency of Parallel Unstructured Finite Element Simulations" , pp. 89-107, Springer-Verlag, 2006
 M. Behr and T. E. Tezduyar, "Finite-Element Solution Strategies for Large-Scale Flow Simulations", Comput. Meth. Appl. Mech. Engineer., vol. 112, pp. 3-24, Feb 1994,
[CrossRef] [Web of Science Times Cited 104]
 C. Giannetti, R. S. Ransing, M. R. Ransing, D. C. Bould, D. T. Gethin, and J. Sienz, "A novel variable selection approach based on co-linearity index to discover optimal process settings by analysing mixed data", Comput. Indust. Engineer., vol. 72, pp. 217-229, 2014,
[CrossRef] [Web of Science Times Cited 9]
 S. Ferreiro, B. Sierra, I. Irigoien, and E. Gorritxategi, "Data mining for quality control: Burr detection in the drilling process", Computers & Industrial Engineering, vol. 60, pp. 801-810, May 2011,
[CrossRef] [Web of Science Times Cited 23]
 M. Luo, H.-C. Yan, B. Hu, J.-H. Zhou, and C. K. Pang, "A data-driven two-stage maintenance framework for degradation prediction in semiconductor manufacturing industries", Comput. Indust. Engineer., vol. 85, pp. 414-422, July 2015,
[CrossRef] [Web of Science Times Cited 16]
 B. Trawinski, M. Smetek, Z. Telec, and T. Lasota, "Nonparametric Statistical Analysis for Multiple Comparison of Machine Learning Regression Algorithms", Int. J. of Appl. Math. and Comp. Sci., vol. 22, pp. 867-881, 2012,
[CrossRef] [Web of Science Times Cited 69]
 J. Luengo, S. Garcia, and F. Herrera, "A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests", Exp. Syst. Appl., vol. 36, pp. 7798-7808, 2009,
[CrossRef] [Web of Science Times Cited 81]
 E. Levin, "A Recurrent Neural Network - Limitations and Training", Proceedings of the 22nd Conference on Information Sciences and Systems, vol. 1-2, pp. 296-301, 1988,
[CrossRef] [Web of Science Times Cited 11]
 H. Cruse, "Neural Networks as Cybernetic Systems", pp. 89-99, Brains, Minds & Media, 2009.
 R. Rojas, "Neural networks: a systematic introduction", pp. 336-348, Springer-verlag, 1996.
 T. Takagi and M. Sugeno, "Fuzzy Identification of Systems and Its Applications to Modeling and Control", IEEE Trans. Sys. Man Cybern., vol. 15, pp. 116-132, 1985,
[CrossRef] [Web of Science Times Cited 11339]
 J. S. R. Jang, "Anfis - Adaptive-Network-Based Fuzzy Inference System", IEEE Trans. Sys. Man Cybern., vol. 23, pp. 665-685, 1993,
[CrossRef] [Web of Science Times Cited 8187]
 F. Wong, "Time Series Forecasting Using Back-Propagation Neural Networks", Neurocomputing, Vol 2, no. 4, 1991, pp. 147-159,
 R. L. MD Richard, "Neural network classifiers estimate Bayesian a posteriori probabilities", IEEE 4 (2) ASSP Magazine, pp. 4-22, 1987,
[CrossRef] [Web of Science Times Cited 564]
 F. Giacometto, E. Sala, K. Kampouropoulos and L. Romeral, "Short-term load forecasting using Cartesian Genetic Programming: An efficient evolutive strategy: Case: Australian electricity market", in IEEE Annual Conference on Industrial Electronics (IECON), pp. 5087-5094, 2015,
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