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Sensoring Leakage Current to Predict Pollution Levels to Improve Transmission Line Model via ANN

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 1 (2017)

DOI
10.11591/ijece.v7i1.pp68-76
ISSN
2088-8708, 2088-8708
Terbit
2017-02-01
Penerbit
Institute of Advanced Engineering and Science
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

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.

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  • University of Technology Malaysia
  • University of Mosul
  • Tafresh University
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Rekan penulisOrganisasiArtikel bersama
Mohammed Ali Abdullah Mohammed Al-RaweUniversity of Mosul2
Haval Sardar KamilUniversity of Technology Malaysia1
Dalila Mat SaidUniversity of Technology Malaysia1
Mohammad Reza MivehTafresh University1
Nasarudin AhmadUniversity of Technology Malaysia1
Ali Abbawi Mohammed AlabbawiAfiliasi tidak diketahui1
Omar Sharaf Al-Deen Al-YozbakyAfiliasi tidak diketahui1
Mohannad Abdulkhaliq AlhubaityUniversity of Mosul1

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Sumber metadata: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, pertama di-harvest 27 Okt 2026, terakhir terlihat 8 Nov 2026.
Metadata sebagai oai_dc, dikonversi dari Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Sensoring Leakage Current to Predict Pollution Levels to Improve Transmission Line Model via ANN</dc:title><dc:creator>I. Khalel, Saraa</dc:creator><dc:creator>Rahmat, Mohd Fadli</dc:creator><dc:creator>Bin Mustafa, Mohd Wazir</dc:creator><dc:description>&lt;jats:p&gt;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.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2017-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v7i1.pp68-76</dc:identifier><dc:identifier>10.11591/ijece.v7i1.pp68-76</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 7 No 1 (2017); 68</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/6254/6010</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>