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Języki publikacji
Abstrakty
Transformers are one of the most important components of the power system. It is important to maintain and assess the condition. Transformer lifetime depends on the life of its insulation and insulation life is also strongly influenced by moisture in the insulation. Due to importance of this issue, in this paper a new method is introduced for determining the moisture content of the transformer insulation system using dielectric response analysis in the frequency domain based on artificial bee colony algorithm. First, the master curve of dielectric response is modeled. Then, using proposed method the master curve and the measured dielectric response curves are compared. By analyzing the results of the comparison, the moisture content of paper insulation, electrical conductivity of the insulating oil and dielectric model dimensions are determined. Finally, the proposed method is applied to several practical samples to demonstrate its capabilities compared with the well-known conventional method.
Czasopismo
Rocznik
Tom
Strony
45--57
Opis fizyczny
Bibliogr. 28 poz., fig., tab.
Twórcy
autor
- Department of Electrical Engineering Zanjan Branch, Islamic Azad University Zanjan, Iran
autor
- Department of Electrical Engineering Zanjan Branch, Islamic Azad University Zanjan, Iran
Bibliografia
- [1] Jadav R.B., Ekanayake C., Saha T.K., Dielectric response of transformer insulation- comparison of time domain and frequency domain measurements. Proc. Int. Conf. IPEC, pp. 199-204 (2010).
- [2] Oommen T.V., Thomas A., Cellulose insulation in oil-filled power transformers: Part II – maintaining insulation integrity and life. IEEE Electrical Insulation Magazine 22(2): 5-14 (2006).
- [3] Saha T.K., Review of modern diagnostic techniques for assessing insulation condition in aged transformers. IEEE Transaction on Dielectrics and Electrical Insulation 10(5): 903-917 (2003).
- [4] Koch M., Krüger M., Tenbohlen S., Comparing Various Moisture Determination Methods For Power Transformers. Proc. Conf. CIGRÉ 6th Southern Africa Regional, Paper P509, (2009).
- [5] Blennow J., Ekanayake C., Walczak K. et al., Field Experiences With Measurements of Dielectric Response in Frequency Domain for Power Transformer Diagnostics. IEEE Transaction on Power Delivery 21(2): 681-68 (2006).
- [6] Ekanayake C., Gubanski S.M., Graczkowski A., Walczak K., Frequency response of oil impregnated pressboard and paper samples for estimating moisture in transformer insulation. IEEE Transaction on Power Delivery 21(3): 1309-1317 (2006).
- [7] Saha T.K., Review of time-domain polarization measurements for assessing insulation condition in aged transformers. IEEE Transaction on Power Delivery 18(4): 1293-1301 (2003).
- [8] Linhjell D., Lundgaard L., Gafvert U., Dielectric response of mineral oil impregnated cellulose and the impact of aging. IEEE Transaction on Dielectrics and Electrical Insulation 14(1): 156-169 (2007).
- [9] Ohlen M., Moisture in power transformers- how to estimate and what to do. Proc. Conf. Transformer Life Management, Megger Sweden AB, Box 724 (2013).
- [10] Suriyah-Jaya M., Leibfried T., Accelerating dielectric response measurements on power transformers. Part II: A regression approach. IEEE Transaction on Power Delivery 29(5): 2095-2100 (2014).
- [11] Karaboga D., Akay B., A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation 214(1): 108-132 (2009).
- [12] Karaboga D., Gorkemli B., Ozturk C., Karaboga N., A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review 42(1): 21-57 (2014).
- [13] Bandara K., Ekanayake Ch., Saha T.K., Modelling the dielectric response measurements of transformer oil. IEEE Transactions on Dielectrics and Electrical Insulation 22(2): 1283-1291 (2015).
- [14] Robalino D.M., Werelius P., Continuous monitoring of power transformer solid insulation dry-out process application of dielectric frequency response. Proc. Conf. Electrical Insulation, pp. 230-234 (2013).
- [15] Gafvert U., Influence of geometric structure and material properties on dielectric frequency response of composite oil cellulose insulation. Proc. Conf. Int. Symposium on Electrical Insulating, pp. 73-76 (2005).
- [16] Hao J., Fu J., Ma Z. et al., Condition assessment of main insulation in transformer by dielectric loss data interpolation method and database building. Proc. Conf. on Electrical Insulating Materials, pp. 152-155 (2014).
- [17] Yew J.H., Pradhan M.K., Saha T.K., Effects of moisture and temperature on the frequency domain spectroscopy analysis of power transformer insulation. Proc. Conf. Power and Energy Society General Meeting, pp.1-8 (2008).
- [18] Ohlen M., Werelius P., Cheng J., Skoldin J., Best practices for dielectric frequency response measurements and analysis in real-world substation environment. Proc. Conf. on Condition Monitoring and Diagnosis, pp. 244-249 (2012).
- [19] Wei G., Saha T.K., Study on moisture in oil-paper insulation by frequency domain spectroscopy. Proc. Conf. Power and Energy Engineering, pp. 1-4 (2011).
- [20] Gubanski S.M., Dielectric response diagnoses for transformer windings. CIGRÉ Task Force D1.01.14 (2010).
- [21] Karlstrom M. et al., Dielectric response measurements in frequency, temperature and time domain. Proc. Conf. TechCon Asia Pacific (2013).
- [22] Chakravorti S. et al., Recent trends in the condition monitoring of transformers. London: Springer-Verlag (2013).
- [23] Liu J., Wang H., Yang F. et al., Influence of geometry to dielectric frequency responses of oil-paper insulation. Proc. Conf. on Solid Dielectrics, Bologna, Italy, pp. 956-959 (2013).
- [24] Karaboga D., An idea based on honey bee swarm for numerical optimization. Technical report TR06, Turkey, Erciyes University, Computer Engineering Department 2005).
- [25] Karaboga D., Basturk B., On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computation 8(1): 687-697 (2008).
- [26] Akay B., Karaboga D., A modified artificial bee colony algorithm for real parameters optimization. Inform Sciences 192(2): 120-142 (2012).
- [27] Badgujar K.P., Maoyafikuddin M., Kulkarni S.V., Alternative statistical techniques for aiding SFRA diagnostics in transformers. IET Generation, Transmission & Distribution 6(3): 189-198 (2012).
- [28] Firoozi H., Bigdeli M., A new method for evaluation of transformer drying process using transfer function analysis and artificial neural network, Archives of Electrical Engineering 62(1): 153-162 (2013).
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę
Typ dokumentu
Bibliografia
Identyfikator YADDA
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