Publisher : The Korean Institute of Electrical Engineers
DOI : 10.5370/JEET.2016.11.4.951
Title & Authors
A Random Forest Model Based Pollution Severity Classification Scheme of High Voltage Transmission Line Insulators Kannan, K.; Shivakumar, R.; Chandrasekar, S.;
Tower insulators in electric power transmission network play a crucial role in preserving the reliability of the system. Electrical utilities frequently face the problem of flashover of insulators due to pollution deposition on their surface. Several research works based on leakage current (LC) measurement has been already carried out in developing diagnostic techniques for these insulators. Since the LC signal is highly intermittent in nature, estimation of pollution severity based on LC signal measurement over a short period of time will not produce accurate results. Reports on the measurement and analysis of LC signals over a long period of time is scanty. This paper attempts to use Random Forest (RF) classifier, which produces accurate results on large data bases, to analyze the pollution severity of high voltage tower insulators. Leakage current characteristics over a long period of time were measured in the laboratory on porcelain insulator. Pollution experiments were conducted at 11 kV AC voltage. Time domain analysis and wavelet transform technique were used to extract both basic features and histogram features of the LC signal. RF model was trained and tested with a variety of LC signals measured over a lengthy period of time and it is noticed that the proposed RF model based pollution severity classifier is efficient and will be helpful to electrical utilities for real time implementation.
V. Jayaprakash Narayanan, M. Sivakumar, K. Karpagavani and S. Chandrasekar, “Prediction of Flashover and Pollution Severity of High Voltage Transmission Line Insulators Using Wavelet Transform and Fuzzy C-Means Approach”, Journal of Electrical Engineering & Technology, vol. 9, no. 5, pp. 1677-1685, 2014.
L. H. Meyer, S. H. Jayaram and E. A. Cherney, “Correlation of damage, dry band arcing energy, and temperature in inclined plane testing of silicone rubber for outdoor insulation”, IEEE Trans. Dielectrics and Electr. Insul., vol. 11, no. 3, pp. 424-432, 2004.
S. H. Kim, E. A. Cherney and R. Hackam, “Hydrophobic behaviour of Insulators Coated with RTV Silicone Rubber”, IEEE Trans. on Electr. Insul., vol. 27, no. 3, pp. 610-622, 1992.
A. Cavallini, S. Chandrasekar and G. C. Montanari, “Inferring Ceramic Insulator Pollution by an innovative Approach Resorting to PD Detection”, IEEE Trans. Dielectrics and Electr. Insul., vol. 14, no. 1, pp. 23-29, 2007.
V. Jayaprakash Narayanan, B. Karthik and S. Chandrasekar, “Flashover Prediction of Polymeric Insulators Using PD Signal Time-Frequency Analysis and BPA Neural Network Technique”, Journal of Electrical Engineering & Technology, vol. 9, no. 4, pp. 1375-1384, 2014.
S. Chandrasekar, C. Kalaivanan, Gian Carlo Montanari and Andrea Cavallini, “Partial Discharge Detection as a Tool to Infer Pollution Severity of Polymeric Insulators”, IEEE Trans. Dielectr. Electr. Insul., vol. 17, no. 1, pp. 181-188, Feb. 2010.
K. Mekala, S. Chandrasekar and R. Samson Ravindran, “Investigations of Accelerated Aged Polymeric Insulators Using Partial Discharge Signal Measurement and Analysis”, Journal of Electrical Engineering & Technology, vol. 10, no. 1, pp. 299-307, 2015.
R. S. Gorur and H. M. Schneider, “Surface resistance measurements on non-ceramic insulators”, IEEE Trans. Power Delivery, vol. 16, pp. 801-805, 2001.
G. Montoya, I. Ramirez, J. I. Montoya, “Correlation among ESDD, NSDD and leakage current in distribution insulators”, IEE Proc. of Generation, Transmission and Distribution, vol. 151, no. 3, pp. 334-340, 2004.
R. Sarathi, S. Chandrasekar and N. Yoshimura, “Investigations into the Surface Condition of the Silicone Rubber Insulation Material using Multiresolution Signal Decomposition”, IEEE Trans. Power Delivery, vol. 21, pp. 243-252, 2006.
Shihua Zhao, Xingliang Jiang, Zhijing Zhang, Jianlin Hu, And Lichun Shu, “Flashover voltage prediction of composite insulators based on the characteristics of leakage current”, IEEE Trans. Power Delivery, vol. 28, no. 3, pp. 1699-1708, 2013.
R.Sarathi and S.Chandrasekar, "Diagnostic study of the surface condition of the insulation structure using wavelet transform and neural networks", Electric Power Systems Research, Elsevier, vol. 68, pp. 137-147, 2004.
T.Suda, “Frequency characteristics of leakage current waveforms of an artificially polluted suspension insulator”, IEEE Trans. Dielectrics and Electr. Insul., vol. 8, no. 4, pp. 705-709, Aug 2001.
M.Ugur, D.W.Auckland, B.R.Varlow, and Z.Emin, “Neural Networks to Analyze Surface Tracking on Solid Insulators”, IEEE Trans. Dielectrics and Electr. Insul., vol. 4, no. 6, pp. 763-766, Dec 1997.
Suwarno, “Leakage Current Waveforms of Outdoor Polymeric Insulators and Possibility of Application for Diagnostics of Insulator Conditions”, Journal of Electrical Engineering & Technology, vol. 1, no. 1, pp. 114-119, 2006.
S.Chandrasekar, C.Kalaivanan, Andrea Cavallini and Gian Carlo Montanari, “Investigations on Leakage Current and Phase Angle Characteristics of Porcelain and Polymeric Insulator under Contaminated Conditions”, IEEE Trans. Dielectr. Electr. Insul., vol. 16, no. 2, pp. 574-583, Apr. 2009.
Leo Brieman and E.Schapire, “Random Forests”, Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.
Weiting Chen, Yu Wang, Guitao Cao, Guoqiang Chen and Qiufang Gu, “A random forest model based classification scheme for neonatal amplitude-integrated ECG”, Biomedical Engineering Online, vol. 13, no. 2, pp. 1-13, 2014
Long Zhenze, "Air-Gap Partial Discharge Development Stage Recognition for Power Transformer Insulation Monitoring Considering Effect of Cavity Size", Theses and Dissertations. Paper 502, UWM Digital Commons, 2014
Musa Al-Hawamdah, “Random Forest”, slideshare, 2012
Jie Mei, Dawei He, Ronald Harley, Thomas Habetler and Guannan Qu, “A Random Forest Method for Real-Time Price Forecasting in New York Electricity Market”, Proceedings of IEEE PES General Meeting Conference, pp.1-5, July 2014
IEC 60507, Artificial Pollution tests on high voltage insulators to be used on AC systems, 1991.