Wind Turbine Blade-Tip Optimization: A Systemic Computational Approach

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Abstract

Curved bladelets on wind turbine blades play an important role in improving the performance and efficiency of wind turbines. Implementing such features on the tip of wind turbine blades can improve their overall aerodynamic characteristics by reducing turbulence and loading without hindering lift generation and overall efficiency, thus leading to increased energy capture and reduced costs over the life of the turbine. Subjecting the integrated blade tip to optimization procedures can maximize its beneficial contribution to the assembly in general. Within this context, a systemic workflow is proposed for the optimization of a curved bladelet implemented on a wind turbine blade. The approach receives input in the form of an initial tip geometry and performs improvements in two distinct stages. Firstly, shape optimization is performed directly on the outer shape to enhance its aerodynamic properties. Subsequently, the topology of its interior structure is refined to decrease its mass while retaining its improved airflow characteristics. The proposed workflow aims to approach blade tip optimization holistically, both in terms of aerodynamic performance and structural capabilities; is computationally validated via fluid dynamics studies and finite element analysis to evaluate the performance augmentation achieved through it; and is further coupled with additive manufacturing for the production of prototype parts, benefiting from the manufacturing flexibility offered by digital fabrication technologies. The optimized bladelet model presented an approximate 30% improvement in the torque generated on it, while maintaining only 70% of its original mass, effectively contributing to a 0.81% increase to the total torque generated by the blade, consequently confirming the effectiveness of the proposed methodology.

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APA

Zouboulis, P., Koumoulos, E. P., & Karatza, A. (2023). Wind Turbine Blade-Tip Optimization: A Systemic Computational Approach. Processes, 11(4). https://doi.org/10.3390/pr11041170

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