Theoretical and Experimental Investigation of Transformer Winding Fault Detection Using Comparison of Transfer Function Coefficients

Mehdi Bigdeli; Mehdi Vakilian; Ebrahim Rahimpour; Davood Azizian

doi:10.37936/ecti-eec.2012101.170436

Authors

Mehdi Bigdeli Department of Electrical Engineering, Science and Research Branch, Islamic Azad University
Mehdi Vakilian Department of Electrical Engineering, Sharif University of Technology
Ebrahim Rahimpour ABB AG, Power Products Division
Davood Azizian Department of Electrical Engineering, Abhar Branch, Islamic Azad University

DOI:

https://doi.org/10.37936/ecti-eec.2012101.170436

Keywords:

Transformer Winding, Axial Displacement, Radial Deformation, Transfer Function Coefficients

Abstract

In this work, a new model of transformer winding is developed. The components in the model are determined by the geometric and electric data of the winding (detailed model) and using experimental data based on genetic algorithm. Under different degrees of axial displacement and radial deformation in the winding, the circuit parameters of the model will change and thus the equivalent circuit characteristics will be influenced. After acquiring the model parameters in the intact and faulted cases, transfer function coefficients are derived in model using nodal analysis. Subsequently, introducing a new index based on these coefficients, the type and extent of penetration of the fault in the winding can be specified. Results presented in this work demonstrate the potential of the proposed method.

References

[1] A. Singh, F. Castellanos, J. R. Marti, and K. D. Srivastava, “A comparison of trans-admittance and characteristic impedance as metrics for detection of winding displacements in power transformers,” Electric Power Systems Research, Elsevier, Vol. 79, No. 1, pp. 871-877, 2009.

[2] T. Leibfried, and K. Feser, “Monitoring of power transformers using the transfer function method,” IEEE Transactions on Power Delivery, Vol. 14, pp. 1333-1341, 1999.

[3] J. Christian, and K. Feser, “Procedures for detecting winding displacements in power transformers by the transfer function methods,” IEEE Transactions on Power Delivery, Vol. 19, pp. 214-220, 2004.

[4] P. M. Nirgude, D. Ashokraju, A. D. Rajkumar, and B. P. Singh, “Application of numerical evaluation techniques for interpreting frequency response measurements in power transformers,” IET Science, Measurements and Technologies, Vol. 2, pp. 275-285, 2008.

[5] E. Rahimpour, J. Christian, K. Feser, and H. Mohseni, “Transfer function method to diagnose axial displacement and radial deformation of transformer winding,” IEEE Transactions on Power Delivery, Vol. 18, pp .493-505, 2003.

[6] P. Karimifard, and G. B. Gharehpetian, “A new algorithm for localization of radial deformation and determination of deformation extent in transformer windings,” Electric Power Systems Research, Elsevier, Vol. 78, pp. 1701-1711, 2009.

[7] A. Miki, T. Hosoya, and K. A. Okuyama, “Calculation method for impulse voltage distribution and transferred voltage in transformer windings,” IEEE Transactions on Power Apparatus and Systems, Vol.PAS-97, No.3, pp. 930-939, 1978.

[8] E. Rahimpour, and M. Bigdeli, “Simplified transient model of transformers based on geometrical dimensions used in power network analysis and fault detection studies,” proceeding of IEEE Second International Conference on Power Engineering, Energy and Electrical Drives (Powereng), Lisbon, Portugal, pp. 375-380, 2009

[9] J. R. Secue, and E. Mombello, “Sweep frequency response analysis (SFRA) for the assessment of winding displacements and deformation in power transformers,” Electric Power Systems Research,
Elsevier, Vol. 78, No. 6, pp. 1119-1128, 2008.

[10] E. Rahimpour, and D. Gorzin, “A new method for comparing the transfer function of transformers in order to detect the location and amount of winding faults,” Electrical Engineering, Springer, Vol. 88, No. 5, pp. 411-416, 2005.

[11] S. A. Ryder, “Transformer diagnosis using frequency response analysis: results from fault simulations,” Proceeding of IEEE Conference on Power Engineering Society, Summer Meeting, pp. 399-404, 2002.

[12] A. Shintemirov, W. H. Tang, and Q. H. Wu, “Transformer winding condition assessment using frequency response analysis and evidential reasoning,” IET Electric Power Applications, Vol. 4, No. 3, pp. 198-212, 2010.

[13] “MATLAB Genetic Algorithm Toolbox,” Version 5, MathWorks Inc, 2006.