Araştırma Makalesi

Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines

Cilt: 8 Sayı: 4 16 Eylül 2025
PDF İndir
EN TR

Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines

Abstract

In this study, This study examines the use of Dynamic Blade Angle Control (DBAC) to improve energy efficiency in wind turbines. DBAC adapts blade pitch based on wind speed fluctuations to optimize energy production while maintaining turbine safety. Using an artificial intelligence-based model, this study analyzes the effects of DBAC on energy efficiency. The model predicts energy production based on wind speed and blade pitch, showing that DBAC increases energy efficiency at low speeds and ensures turbine safety at high speeds. The model's performance is enhanced with feedforward control strategies and LiDAR-assisted systems. These results emphasize the importance of DBAC and AI-based control systems in enhancing energy efficiency in wind turbines

Keywords

Kaynakça

  1. Abouheaf M., Gueaieb W., Sharaf A. Model-free adaptive learning control scheme for wind turbines with doubly fed induction generators. IET Renewable Power Generation. 2018; 12(14): 1675-1686.
  2. Bossanyi E., Leithead W., Gaunaa M. Impact of multi-axis control on wind turbine efficiency. Wind Energy. 2023; 46: 123-135.
  3. Bottasso C., Wang L. Enhancing wind turbine stability with advanced pitch control algorithms. Journal of Renewable and Sustainable Energy. 2023; 15(3): 230-239.
  4. David F., Steffen H. Comparative study on neural network-based and traditional pitch control. Energy Reports. 2023; 10: 127-138.
  5. Fernandez-Gauna B., Fernandez-Gamiz U. Variable speed wind turbine controller adaptation by reinforcement learning. Integrated Computer-Aided Engineering. 2017; 24(1): 27-39.
  6. Haizmann F., Bauer N., Brücke T. Model predictive control for blade pitch optimization. Renewable Energy Journal. 2022; 75: 258-270.
  7. Harris M., Cole S., Good M. Longitudinal velocity estimation using nacelle-mounted lidar systems. Renewable Energy Journal. 2023; 35: 457-470.
  8. Khaniki R., Azadi M., Faghihimani M. LiDAR-based wind prediction for feedforward pitch control. Journal of Wind Engineering. 2023; 30(2): 112-125.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Rüzgar Enerjisi Sistemleri

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

16 Eylül 2025

Gönderilme Tarihi

16 Ekim 2024

Kabul Tarihi

6 Nisan 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 8 Sayı: 4

Kaynak Göster

APA
Yönetken, A., & Kosova, İ. (2025). Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 8(4), 1654-1669. https://doi.org/10.47495/okufbed.1568705
AMA
1.Yönetken A, Kosova İ. Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2025;8(4):1654-1669. doi:10.47495/okufbed.1568705
Chicago
Yönetken, Ahmet, ve İdris Kosova. 2025. “Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8 (4): 1654-69. https://doi.org/10.47495/okufbed.1568705.
EndNote
Yönetken A, Kosova İ (01 Eylül 2025) Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8 4 1654–1669.
IEEE
[1]A. Yönetken ve İ. Kosova, “Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines”, Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 8, sy 4, ss. 1654–1669, Eyl. 2025, doi: 10.47495/okufbed.1568705.
ISNAD
Yönetken, Ahmet - Kosova, İdris. “Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi 8/4 (01 Eylül 2025): 1654-1669. https://doi.org/10.47495/okufbed.1568705.
JAMA
1.Yönetken A, Kosova İ. Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2025;8:1654–1669.
MLA
Yönetken, Ahmet, ve İdris Kosova. “Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines”. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 8, sy 4, Eylül 2025, ss. 1654-69, doi:10.47495/okufbed.1568705.
Vancouver
1.Ahmet Yönetken, İdris Kosova. Investigation of Energy Efficiency with Artificial Intelligence Based Dynamic Blade Angle Control for Wind Turbines. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 01 Eylül 2025;8(4):1654-69. doi:10.47495/okufbed.1568705

23487




196541947019414  

1943319434 19435194361960219721 19784  2123822610 23877

* Uluslararası Hakemli Dergi (International Peer Reviewed Journal)

* Yazar/yazarlardan hiçbir şekilde MAKALE BASIM ÜCRETİ vb. şeyler istenmemektedir (Free submission and publication).

* Yılda Ocak, Mart, Haziran, Eylül ve Aralık'ta olmak üzere 5 sayı yayınlanmaktadır (Published 5 times a year)

* Dergide, Türkçe ve İngilizce makaleler basılmaktadır.

*Dergi açık erişimli bir dergidir.

Creative Commons License

Bu web sitesi Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmıştır.