Khalel, S. I. and Rahmat, M. F. and Mustafa, M. W. B. (2017) Sensoring leakage current to predict pollution levels to improve transmission line model via ANN. International Journal of Electrical and Computer Engineering, 7 (1). pp. 68-76. ISSN 2088-8708
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Abstract
Pollution insulator is a serious threat to the safety operations of electric power systems. Leakage current detection is widely employed in transmission line insulators to assess pollution levels. This paper presents the prediction of pollution levels on insulators based on simulated leakage current and voltage in a transmission tower.The simulation parameters are based on improved transmission line model with leakage current resistance insertion between buses. Artificial neural network (ANN) is employed to predict the level of pollution with different locations of simulated leakage current and voltage between two buses. With a sufficient number of training, the test results showed a significant potential for pollution level prediction with more than 95% Correct Classification Rate (CCR) and output of the ANN showed high agreement with Simulink results.
Item Type: | Article |
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Uncontrolled Keywords: | ANN, Insulator, Leakage current, Predict level pollution, Sensoring |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 77101 |
Deposited By: | Fazli Masari |
Deposited On: | 30 Apr 2018 14:39 |
Last Modified: | 30 Apr 2018 14:39 |
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