Prediction by artificial neural networks analysis of emergency situations at wind farms
In this study, the Siemens wind turbine was analyzed according to technical specifications using artificial neural networks, and the possible forecasts of the wind turbine going out of service for maintenance due to mechanical and electrical faults, control systems, and other faults such as disconne...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_01009.pdf |
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| author | Al-Haidari Zaid Salah Al-Yaqoubi Diaa Abdel Karim Fakher Osintsev Konstantin |
| author_facet | Al-Haidari Zaid Salah Al-Yaqoubi Diaa Abdel Karim Fakher Osintsev Konstantin |
| author_sort | Al-Haidari Zaid Salah |
| collection | DOAJ |
| description | In this study, the Siemens wind turbine was analyzed according to technical specifications using artificial neural networks, and the possible forecasts of the wind turbine going out of service for maintenance due to mechanical and electrical faults, control systems, and other faults such as disconnection from the electrical network were studied and the role of preventive maintenance based on this forecast is explained. From energy losses due to the turbine being out of operation for maintenance |
| format | Article |
| id | doaj-art-e1c0f3560b7e455db1aa2a85de0a6bd7 |
| institution | DOAJ |
| issn | 2267-1242 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-e1c0f3560b7e455db1aa2a85de0a6bd72025-08-20T03:12:46ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016140100910.1051/e3sconf/202561401009e3sconf_icaw2024_01009Prediction by artificial neural networks analysis of emergency situations at wind farmsAl-Haidari Zaid Salah0Al-Yaqoubi Diaa Abdel Karim Fakher1Osintsev Konstantin2Ministry of Electricity and Renewable Energy - General Company for Electric Power Production Medial RegionUniversity of TabrizSouth Ural State UniversityIn this study, the Siemens wind turbine was analyzed according to technical specifications using artificial neural networks, and the possible forecasts of the wind turbine going out of service for maintenance due to mechanical and electrical faults, control systems, and other faults such as disconnection from the electrical network were studied and the role of preventive maintenance based on this forecast is explained. From energy losses due to the turbine being out of operation for maintenancehttps://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_01009.pdf |
| spellingShingle | Al-Haidari Zaid Salah Al-Yaqoubi Diaa Abdel Karim Fakher Osintsev Konstantin Prediction by artificial neural networks analysis of emergency situations at wind farms E3S Web of Conferences |
| title | Prediction by artificial neural networks analysis of emergency situations at wind farms |
| title_full | Prediction by artificial neural networks analysis of emergency situations at wind farms |
| title_fullStr | Prediction by artificial neural networks analysis of emergency situations at wind farms |
| title_full_unstemmed | Prediction by artificial neural networks analysis of emergency situations at wind farms |
| title_short | Prediction by artificial neural networks analysis of emergency situations at wind farms |
| title_sort | prediction by artificial neural networks analysis of emergency situations at wind farms |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_01009.pdf |
| work_keys_str_mv | AT alhaidarizaidsalah predictionbyartificialneuralnetworksanalysisofemergencysituationsatwindfarms AT alyaqoubidiaaabdelkarimfakher predictionbyartificialneuralnetworksanalysisofemergencysituationsatwindfarms AT osintsevkonstantin predictionbyartificialneuralnetworksanalysisofemergencysituationsatwindfarms |