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

Year 2025, Volume: 8 Issue: 4, 1654 - 1669, 16.09.2025

Ahmet Yönetken , İdris Kosova

https://doi.org/10.47495/okufbed.1568705

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

Dynamic Blade Angle Control , Wind Turbines , Energy Efficiency , Artificial Intelligence , Machine Learning , LiDAR

Rüzgâr Türbinleri İçin Yapay Zekâ Tabanlı Dinamik Kanat Açısı Kontrolü ile Enerji Verimliliğinin Araştırılması

Abstract

Bu çalışmada, rüzgar türbinlerinde enerji verimliliğini artırmak için Dinamik Kanat Açısı Kontrolü (DKAK) yöntemini incelemektedir. Rüzgar hızındaki değişimlere göre kanat açısının uyarlanmasını sağlayan DKAK, türbin güvenliğini korurken enerji üretimini optimize etmeyi amaçlamaktadır. Çalışmada, yapay zeka destekli bir model kullanılarak DKAK’nin enerji verimliliği üzerindeki etkileri analiz edilmiştir. Rüzgar hızı ve kanat açısına bağlı olarak enerji üretim tahminleri yapan model, düşük hızlarda DKAK'nin enerji verimliliğini artırdığını, yüksek hızlarda ise türbin güvenliğini sağladığını göstermektedir. Modelin performansı, ileri beslemeli kontrol stratejileri ve LiDAR destekli sistemler ile güçlendirilmiştir. Bu sonuçlar, rüzgar türbinlerinde enerji verimliliğini artırmak için DKAK ve yapay zeka tabanlı kontrol sistemlerinin önemini vurgulamaktadır.

Keywords

Dinamik Kanat Açısı Kontrolü , Rüzgar Türbinleri , Enerji Verimliliği , Yapay Zeka , Makine Öğrenmesi , LiDAR

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