Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network
Transformers are important parts of an electrical power system. When a power transformer is connected to the grid, usually inrush current increases substantially with a high value of harmonic components with a duration up to many cycles. The amount of flux in the core increases causing the magnetic...
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Wasit University
2024-12-01
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| Series: | Wasit Journal of Engineering Sciences |
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| Online Access: | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/568 |
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| author | Hussein A. Taha |
| author_facet | Hussein A. Taha |
| author_sort | Hussein A. Taha |
| collection | DOAJ |
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Transformers are important parts of an electrical power system. When a power transformer is connected to the grid, usually inrush current increases substantially with a high value of harmonic components with a duration up to many cycles. The amount of flux in the core increases causing the magnetic circuit to saturate due to the increasing in the load. This paper describes a technique to accurately predict the inrush current and third harmonic of three phase transformer. A shallow neural network was created. The input parameters of the artificial neural network were the magnetization resistance Rm, the initial flux of phase A and the switching angle q. The number of neurons has been changed in the code to see the best performance value. The best validation performance was at epoch 71 with a value of 5.3641e-05. A good prediction results were obtained using this ANN. The simulation of the inrush current was done using the MATLAB Simulink software.
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| format | Article |
| id | doaj-art-c06fbbf845af4ac3a4d648fde549b869 |
| institution | DOAJ |
| issn | 2305-6932 2663-1970 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wasit University |
| record_format | Article |
| series | Wasit Journal of Engineering Sciences |
| spelling | doaj-art-c06fbbf845af4ac3a4d648fde549b8692025-08-20T02:40:17ZengWasit UniversityWasit Journal of Engineering Sciences2305-69322663-19702024-12-0112410.31185/ejuow.Vol12.Iss4.568Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural NetworkHussein A. Taha0Department of Electrical Engineering, Wasit University Transformers are important parts of an electrical power system. When a power transformer is connected to the grid, usually inrush current increases substantially with a high value of harmonic components with a duration up to many cycles. The amount of flux in the core increases causing the magnetic circuit to saturate due to the increasing in the load. This paper describes a technique to accurately predict the inrush current and third harmonic of three phase transformer. A shallow neural network was created. The input parameters of the artificial neural network were the magnetization resistance Rm, the initial flux of phase A and the switching angle q. The number of neurons has been changed in the code to see the best performance value. The best validation performance was at epoch 71 with a value of 5.3641e-05. A good prediction results were obtained using this ANN. The simulation of the inrush current was done using the MATLAB Simulink software. https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/568three phase transformerartificial neural network, inrush current |
| spellingShingle | Hussein A. Taha Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network Wasit Journal of Engineering Sciences three phase transformer artificial neural network, inrush current |
| title | Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network |
| title_full | Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network |
| title_fullStr | Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network |
| title_full_unstemmed | Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network |
| title_short | Eliminating Inrush Current in Three-Phase Transformer using Artificial Neural Network |
| title_sort | eliminating inrush current in three phase transformer using artificial neural network |
| topic | three phase transformer artificial neural network, inrush current |
| url | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/568 |
| work_keys_str_mv | AT husseinataha eliminatinginrushcurrentinthreephasetransformerusingartificialneuralnetwork |