Reliability Enhancement of Line Insulator of a Transmission System using Artificial Neural Network
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2016 by IJETT Journal|
|Year of Publication : 2016|
|Authors : Sumit Mathur, G.K. Joshi
|DOI : 10.14445/22315381/IJETT-V41P262|
Sumit Mathur, G.K. Joshi "Reliability Enhancement of Line Insulator of a Transmission System using Artificial Neural Network", International Journal of Engineering Trends and Technology (IJETT), V41(7),341-346 November 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
The line insulators which hold the transmission line conductor suffer degradation in dielectric quality due to pollution. The pollution is caused because of the formation of layers of salt, chemicals, dust and oil etc. on the surface of dielectric. This pollution affects the resistance and capacitance of the dielectric and therefore Tan? which increases with pollution. Also when the growth in Tan? exceeds the threshold value of Tan? for the insulator, it loses reliability. The aim of the present paper is to assess the reliability by monitoring growth in Tan?. The insulators are washed with water to check the growth in pollution and to enhance the reliability of insulator. Washing controls the growth of pollution and therefore growth of Tan?. The Tan? therefore takes longer time to attain its threshold value. The insulator therefore loses its reliability at a later point of time thus ensuring reliability enhancement. The reliability enhancement of insulator due to control in growth of Tan? is also confirmed through Artificial Neural Network.
1. P.J. Lambeth, “Variable-Voltage Application for Insulator Pollution Tests” IEEE Transactions on Power Delivery, Vol. 3, No. 4, pp.2103-2111,October 1988.
2. L. A. Dissado, “Predicting Electrical Breakdown in Polymeric Insulators,” IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 9, No. 5, pp. 860-875, October 2002.
3. M. Kumosa, L. Kumosa and D. Armentrout, “Failure analyses of composite (non-ceramic) insulators: Part I—Brittle fracture characteristics,” IEEE Electrical Insulation Magazine, vol. 21, no. 3, pp. 14–27, May/Jun. 2005.
4. M. Kumosa, L. Kumosa, and D. Armentrout, “Failure Analyses of Nonceramic Insulators: Part II—The Brittle Fracture Model and Failure Prevention,” IEEE Electrical Insulation Magazine, Vol. 21, No. 4, pp. 28-41, July/August 2005.
5. G. Mazzanti, G.C. Montanari and L. A. Dissado, “Electrical Aging and Life Models: The Role of Space Charge,” IEEE Transactions on Dielectrics and Electrical Insulation Vol. 12, No. 5; pp.876-890, October 2005.
6. C. Roggendorf and A. Schnettler, “Accelerated Hydrothermal Aging of Epoxy Resin Based Syntactic Foams with Polymeric Microspheres” IEEE Transactions on Dielectrics and Electrical Insulation Vol. 19, No. 3;pp.973-980, June 2012.
7. K. Wieczorek, J. Fleszynski and W. Bretuj, “Effect of Shape of Insulator Housings and Positions of Composite Insulators on Ageing Resistance under High Voltage and Precipitation” IEEE Transactions on Dielectrics and Electrical Insulation Vol. 19, No. 3;pp.1044-1052, June 2012.
Dissipation factor, Tan?, Loss factor, Pollution factor, Periodic Washing, Reliability, Artificial Neural Network (ANN).