Intelligent Diagnostic Method for Ageing Analysis of Transformer

Anil Kumar Kori, Arvind Kumar Sharma, Ashok Kumar Singh Bhadoriya

Department of Electrical Engineering, Jabalpur Engineering College, Jabalpur, Indi.
Department of Electrical Engineering, Jabalpur Engineering College, Jabalpur, India.
Rajiv Gandhi Technical University, Bhopal, India.

DOI: 10.4236/epe.2012.42008                

Abstract

The fuzzy method is proposed for ageing analysis of transformer. The fuzzy controller is used for various input and one output, strictly depends on the number of membership function and there rule base and the type of the defuzzification method. The ageing of transformers is influenced by short term and long term over loads, number and intensity of short circuits, incidence of lightning, and internal faults. The recent development of various techniques for detecting the incipient fault conditions have been improved to some extent; the life expectancy of transformers by resorting to corrective actions in time. The ageing behavior is likely to be different for different types of transformers. The life span of the transformer, thus depends initially on the design and quality of manufacture and later on service conditions and maintenance standard, these factors vary considerably and affect the useful span of service life which therefore needs to be taken into account for residual life assessment. During the natural ageing of transformers, the insulation of winding deteriorates. Cellulose insulation degrades due to heating or electrical breakdown which is dissolved in oil. Hence, the chemical analysis of the Transformer oil gives evidence of changes that are taking place in the winding insulation during operation. Deterioration in transformer cellulose decreases both its electrical and mechanical strength. In this paper a novel fuzzy based algorithm has been implemented on three samples of power transformer oil.

Keywords

Transformer Oil; Paper Insulation; Electrical Breakdown; Ageing Analysis; Fuzzy Logic Controller

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	J.-D. Cal and T. Zhang, “Moisture Content Assessment of Transformer Solid Insulation using Return Voltage Spectrum,” Proceedings of the 26th Annual International Conference on Properties and Applications of Dielectric Materials, Harbin, 19-23 July 2009, pp. 257-260. doi:10.1109/ICPADM.2009.5252457
[2]	B. García, J. C. Burgos, á. M. Alonso and J. Sanz, “A Moisture-in-Oil Model for Power Transformer Monitoring-Part II: Experimental Verification,” IEEE Transaction on Power Delivery, Vol. 20, No. 2, 2005, pp. 1423-1429. doi:10.1109/TPWRD.2004.832361
[3]	V. Mentlík, P. Prosr, R. Polansky, J. Michalík and M. Brandt “Instruments for Online Monitoring of Transformers,” International Conference on Renewable Energies and Power Quality, Valencia, 15-17 April 2009, pp. 1-5.
[4]	M. Mirzaie, A. Gholami and H. R. Tayebi, “Insulation Condition Assessment of Power Transformers Using Accelerated Ageing Tests,” Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 17, No. 1, 2009, 39-54.
[5]	D. Ming, Z. M. Ge, Q. Y. Ming and Y. Zhang “Ageing Diagnosis and Lifetime Estimation for Power Transformer,” Proceeding of the 14th International Symposium on High Voltage Engineering, Beijing, 25-29 August 2005, pp. 1-5.
[6]	H.-Z. Ding, Z. D. Wang and P. Jarman, “Dielectric Strength of Aged Transformer Oil Experimental Studies and Statistical Analysis of Breakdown Voltage,” Proceeding of the 14th International Symposium on High Voltage Engineering, Beijing, 25-29 August 2005, pp. 1-5.
[7]	H. P. Gasser, B. Heinrich and C. Krause “Condition Assessment of the Cellulosic Insulation from Power Transformer Taken out for Service,” Proceeding of the 14th International Symposium on High Voltage Engineering, Beijing, 25-29 August 2005, pp. 1-5.
[8]	M. Butcher, M. D. Cevallos and H. Krompholz, “Conduction and Breakdown Mechanisms in Transformer Oil,” IEEE Transaction on Plasma Science, Vol. 34, No. 2, 2006, pp. 467-475. doi:10.1109/TPS.2006.872487
[9]	M. Arshad, S. M.Islam and Abdul Khalique, “Power Transformer Aging and Life Extension,” 8th International Conference on Probabilistic Methods Applied to Power Systems, Ames, 12-16 September 2004, pp. 498-501.
[10]	V. Duraisamy, N. Devarajan, D. Somasundareswari, A. A. M. Vasanth and S. N. Sivanandam, “Neuro Fuzzy Schemes for Fault Detection in Power Transformer,” Applied Soft Computing, Vol. 7, No. 2, 2007, pp. 534-539. doi:10.1016/j.asoc.2006.10.001
[11]	W. C. Floresa, E. Mombello, J. A. Jardinic and G. Rattá “Fuzzy Risk Index for Power Transformer Failures Due to External Short-Circuits,” Electric Power Systems Research, Vol. 79, No. 4, 2009, pp. 539-549. doi:10.1016/j.epsr.2008.06.021