Supervised artificial neural networks by field-oriented control applied to PMSG-based variable-speed wind turbine
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of electrical and electronics engineers inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Artificial intelligence techniques (AI), especially Artificial Neural Networks (ANN), have a significant impact on the control of electrical machines and power systems. Neural networks have created new and advanced boundaries in controlling power systems and electric generators, and they are already a complex, multidisciplinary technology undergoing dynamic evolution in recent years. This paper presents the application of a control methodology to a permanent magnet synchronous generator (PMSG) in the context of a variable speed wind turbine system. The study particularly focused on exploring the performance and optimization of the wind turbine system through the use of this control approach to extract the maximum amount of variable speed wind energy and address associated errors and problems, the control being studied and applied is Supervised ANN by FOC. The discussion explored the various components and performance of a wind system (WS) through simulations conducted in MATLAB/Simulink.
Açıklama
Anahtar Kelimeler
Artificial Neural Networks (ANN), Field- Oriented Control (FOC), Permanent Magnet Synchronous Generators (PMSG), Wind System
Kaynak
12th international conference on smart grid, icSmartGrid 2024
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Aoumri, M., Harrouz, A., Yaichi, I., Colak, I., Kayisli, K., & Dumbrava, V. (2024, May). Supervised Artificial Neural Networks by Field-Oriented Control applied to PMSG-based Variable-Speed Wind Turbine. In 2024 12th International Conference on Smart Grid (icSmartGrid) (pp. 187-191). IEEE.
