کنفرانس بین المللی ماشین و محرکه های الکتریکی

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صفحه اصلی / icemd2024

Dynamic Grid Search Optimization for ANFIS-Based Wind Turbine Control: Enhancing Efficiency and Adaptability

نویسندگان :

Ali Najari¹ Ava Zanir² Maryam Jabari³ Mohammad Jabari⁴

1- Sapienza University of Rome 2- دانشگاه تهران 3- دانشگاه تهران 4- دانشگاه بوعلی سینا

کلمات کلیدی :

Wind Turbine Control،Adaptive Neuro-Fuzzy Inference System (ANFIS)،Grid Search with Dynamic Constraints،Variable Speed Turbine،Renewable Energy

چکیده :

The effective performance of variable-speed wind turbines is crucial for enhancing energy production efficiency and minimizing mechanical stress caused by fluctuating wind conditions. This paper examines the integration of an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a novel grid search-based dynamic constraint optimization approach for hyperparameter tuning. The proposed method dynamically narrows the hyperparameter search space based on real-time system behavior, enabling efficient tuning without exhaustive computational effort. Comparative evaluations using actual wind turbine data demonstrate significant improvements in power output, system accuracy, and computational efficiency. The results confirm that the optimized ANFIS model outperforms conventional methods, offering a scalable solution for real-world energy systems. This approach also highlights its potential for reducing turbine maintenance costs and improving lifespan under varying wind speeds.