Identificación del Modelo No Lineal propuesto por el MIT para Transformadores de Potencia aplicando Algoritmos Genéticos (Identification of the Nonlinear Model proposed by the MIT for Power Transformer applying Genetic Algorithms)

Romulo Jose Perez Barrios (romuloperez2003@gmail.com)1, Enrique Matos (gardero@gmail.com)2, Sergio Jesus Férnandez Garcia (sfg@electrica.cujae.edu.cu)3


1Universidad Nacional Experimental Politécnica “Antonio José de Sucre” UNEXPO, Venezuela
2Universidad de Cienfuegos, Cuba.
3Centro de Investigaciones y Pruebas Electroenergéticas CIPEL-CUJAE, Cuba

This paper appears in: Revista IEEE América Latina

Publication Date: Dec. 2009
Volume: 7,   Issue: 6 
ISSN: 1548-0992


Abstract:
This paper present a technique based on Genetic Algorithms for nonlinear model parameters estimation proposed by the MIT (Massachusetts Institute of Technology) for top oil temperature prediction in power transformers that is being used in an on-line monitoring and diagnosis system installed in an 100 MVA autotransformer of Barquisimeto Substation ENELBAR Venezuela since 2003. The results of the parameters estimation by genetic algorithms are compared with previous results obtained by the parameters estimation made with Linear Minimum Square and the real measurements of the top oil temperature. Results are discussed and this model is proposed for top oil temperature prediction and diagnosis tool.

Index Terms:
genetic algorithms, parameters estimation, power transformers, diagnosis.   


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