Optimizing Neuro-Fuzzy Approach of Internal Fault Recognition in Power Transformers by Genetic Algorithm
Publish place: Fourth International Conference on Modern Research in Engineering Sciences and Technology
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NSOECE04_187
تاریخ نمایه سازی: 9 مرداد 1395
Abstract:
Transformer is one of the important devices in power systems and failure occurrence in transformer can lead to the long service interruptions as well as costly repairs. According to their importance for electric energy transferring, awareness of insulating oil condition is highly important for transformers. Studying the dissolved gases in oil can be an effective and beneficial approach to diagnose internal failures of transformers prior to irreparable failure occurrences. The results of studies about dissolved gases in oil are interpreted by experienced technicians, former experiences, and standard approaches. In this article, neural-fuzzy system is used to diagnose internal failure of transformer and dissolved gases in oil ratio. Finally, Genetic optimizing algorithm is used to improve the results.
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Authors
Abdollah Mirzabeigi
M.S of Control Engineering, Knowelede and Industry University of Tehran. Faculty member of Science and Culture Hamedan University
Shirzad Jamshidi
B.A of Power Engineering, Islamic Azad University of Najaf abad. .Manager of Hamedan Power Energy Distribution
Seyed Mahdi Hosseini3
M.S of Power engineering, Islamic Azad University of Arak. Supervisor of Hamedan Power Energy Distribution
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