Estimation of Moisture in Transformer Insulation Using Dielectric Frequency Response Analysis by Heuristic Algorithms

Document Type : Research Paper


1 Islamic Azad University

2 Iran Transfo Company


Transformers are one of the most valuable assets of power systems. Maintenance and condition assessment of transformers has become one of the concerns of researchers due to a huge number of transformers has been approached to the end of their lifetimes. Transformer’s lifetime depends on the life of its insulation and the insulation’s life is strongly influenced by its moisture attraction as well. Thus, regarding the importance of moisture analysis, in this paper, a new method is introduced for moisture content determination in the transformer insulation system. The introduced method uses the dielectric response analysis in the frequency domain based on heuristic algorithms such as genetic algorithm and particle swarm optimization. First, the master curve of the dielectric response is modeled. Afterward, using the proposed method the master curve and the measured dielectric response curves are compared. By analyzing the comparison results, the moisture content of the paper insulation, the electrical conductivity of the insulating oil, and the dielectric model dimensions are determined. Finally, the proposed methods are applied to several practical samples and their capabilities are compared to the well-known conventional method.


[1]      R. B. Jadav, C. Ekanayake, T. K. Saha, “Dielectric response of transformer insulation- comparison of time domain and frequency domain measurements”, Proc. Int. Conf. IPEC, 2010, pp. 199-204.
[2]      T. V. Oommen, A. Thomas, “Cellulose insulation in oil-filled power transformers: Part II – maintaining insulation integrity and life”, IEEE Electrical Insulation Magazine, Vol. 22, No. 2, 2006, pp. 5-14.
[3]      T. K. Saha, “Review of modern diagnostic techniques for assessing insulation condition in aged transformers”, IEEE Transaction on Dielectrics and Electrical Insulation, Vol. 10 No. 5, 2003, pp. 903-917.
[4]      M. Koch, M. Krüger, S. Tenbohlen, “Comparing Various Moisture Determination Methods for Power Transformers”, Proc. Conf. CIGRÉ 6th Southern Africa Regional, 2009, Paper P509.
[5]      J. Blennow, C. Ekanayake, K. Walczak, B. Garcia, S. M. Gubanski, “Field Experiences with Measurements of Dielectric Response in Frequency Domain for Power Transformer Diagnostics”, IEEE Transaction on Power Delivery, Vol. 21, No. 2, 2006, pp. 681-68.
[6]      C. Ekanayake, S. M. Gubanski, A. Graczkowski, K. Walczak, “Frequency response of oil impregnated pressboard and paper samples for estimating moisture in transformer insulation”, IEEE Transaction on Power Delivery, Vol. 21, No. 3, 2006, pp. 1309-1317.
[7]      T. K. Saha, “Review of time-domain polarization measurements for assessing insulation condition in aged transformers”, IEEE Transaction on Power Delivery, Vol. 18, No. 4, 2003, pp. 1293-1301.
[8]      D. Linhjell, L. Lundgaard, U. Gafvert, “Dielectric response of mineral oil impregnated cellulose and the impact of aging”, IEEE Transaction on Dielectrics and Electrical Insulation, Vol. 14, No. 1, 2007, pp. 156-169.
[9]      R. Liao, J. Liu, L. Yang, J. Gao, Y. Zhang, Y. Dong, H. Zheng, “Understanding and analysis on frequency dielectric parameter for quantitative diagnosis of moisture content in paper–oil insulation system”, IET Electric Power Applications, Vol. 9, No. 3, 2015, pp. 213-222.
[10]   X. Yang, Sh. Nielsen, G. Ledwich, “Investigations of dielectric monitoring on an energized transformer oil–paper insulation system”, IET Science, Measurement and Technology, Vol. 9, No. 1, 2015, pp. 102-112.
[11]   R. Nikjoo, N. Taylor, R. C. Kiiza, H. Edin, “Dielectric response of oil-impregnated paper by utilizing lightning and switching transients, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 1, 2015, pp: 335-344.
[12]   A. Betie, F. Meghnefi, I. Fofana, Z. Yeo, H. Ezzaidi, “Neural network approach to separate aging and moisture from the dielectric response of oil impregnated paper insulation, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 4, 2015, pp. 2176-2184.
[13]   M. Ohlen, “Moisture in power transformers- how to estimate and what to do, Proc. Conf. Transformer Life Management”, Megger Sweden AB, 2013, Box 724.
[14]   M. Suriyah-Jaya, T. Leibfried, “Accelerating dielectric response measurements on power transformers—Part II: A regression approach”, IEEE Transaction on Power Delivery, Vol. 29, No. 5, 2014, pp. 2095-2100.
[15]   K. Bandara, Ch. Ekanayake, T. K. Saha, “Modelling the dielectric response measurements of transformer oil”, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 2, 2015, pp. 1283-1291.
[16]   D. M. Robalino, P. Werelius, “Continuous monitoring of power transformer solid insulation dry-out process application of dielectric frequency response”, Proc. Conf. Electrical Insulation, 2013, pp. 230 – 234.
[17]   U. Gafvert, “Influence of geometric structure and material properties on dielectric frequency response of composite oil cellulose insulation”, Proc. Conf. Int. Symposium on Electrical Insulating, 2005, pp.73-76.
[18]   J. Hao, J. Fu, Z. Ma, S. Zhang, J. Shen, “Condition assessment of main insulation in transformer by dielectric loss data interpolation method and database building”, Proc. Conf. on Electrical Insulating Materials, 2014, pp. 152 - 155.
[19]   J. H. Yew, M. K. Pradhan, T. K. Saha, “Effects of moisture and temperature on the frequency domain spectroscopy analysis of power transformer insulation”, Proc. Conf. Power and Energy Society General Meeting, 2008, pp.1-8.
[20]   M. Ohlen, P. Werelius, J. Cheng, J. Skoldin, “Best practices for dielectric frequency response measurements and analysis in real-world substation environment”, Proc. Conf. on Condition Monitoring and Diagnosis, 2012, pp. 244-249.
[21]   G. Wei, T. K. Saha, “Study on moisture in oil-paper insulation by frequency domain spectroscopy”, Proc. Conf. Power and Energy Engineering, 2011, pp. 1-4.
[22]   S. M. Gubanski, “Dielectric response diagnoses for transformer windings”, CIGRÉ Task Force D1.01.14, 2010.
[23]   M. Karlstrom, et al., “Dielectric response measurements in frequency, temperature and time domain”, Proc. Conf. TechCon Asia Pacific, 2013.
[24]   S. Chakravorti, et al., “Recent trends in the condition monitoring of transformers”, London: Springer- Verlag, 2013.
[25]   J. Liu, H. Wang, F. Yang, H. Zhang, X. Yang, C. Cai, P. Wang, “Influence of geometry to dielectric frequency responses of oil-paper insulation”, Proc. Conf. on Solid Dielectrics, Bologna, Italy, 2013, pp. 956-959.
[26]   D. E. Goldberg, “Genetic algorithms in search, optimization and machine learning”, Addison Wesley Publishing Company, Ind. USA, 1989.
[27]   A. Raie, V. Rashtchi, “Using a genetic algorithm for detection and magnitude determination of turn faults in an induction motor”, Electrical Engineering, Springer Verlag, Vol. 84, No. 5, 2002, pp. 275–279.
[28]   J. Kennedy, R. Eberhart, “Particle Swarm Optimization”, IEEE Int. Conf. on Neural Networks, Perth, Australia, Vol. 4, 1995, pp. 1942-1948.
[29]   Y. Shi, R. Eberhart, “Empirical study of particle swarm optimization”, Proceeding of the 1999 Congress on Evolutionary Computation, CEC 99, Vol. 3, 1999, pp. 1945-1950.
[30]   Y. Zheng, L. Ma, L. Zhang, I. Qian, “On the convergence analysis and parameter selection in particle swarm optimization”, in Proc. Int. Conf. Machine Learning Cybern, 2003, pp.1802-1807.
[31]   M. Clerc, J. Kenndy, “The Particle swarm-explosion, stability, and convergence in a multidimensional complex space”, IEEE Transaction on Evolutionary Computation, Vol. 6, No. 2, 2002, pp. 58-73.
[32]   K. P. Badgujar, M. Maoyafikuddin, S. V. Kulkarni, “Alternative statistical techniques for aiding SFRA diagnostics in transformers”, IET Generation, Transmission & Distribution, Vol. 6, No. 3, 2012, pp. 189–198.
[33]   H. Firoozi, M. Bigdeli, “A new method for evaluation of transformer drying process using transfer function analysis and artificial neural network”, Archives of Electrical Engineering, Vol. 62, No. 1, 2013, pp. 153-162.