A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high Levelized Cost of Energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor's performance and the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function, is provided by the definition of a surrogate model. An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15MW wind turbine blade optimized for specific deepwater sites in the Mediterranean Sea.
Aerodynamic design of wind turbine blades using multi-fidelity analysis and surrogate models / Cardamone R.; Broglia R.; Bianchini A.; Papi F.; Rispoli F.; Corsini A.; Castorrini A.. - ELETTRONICO. - (2025), pp. 0-0. ( 16th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics, ETC 2025 deu 2025).
Aerodynamic design of wind turbine blades using multi-fidelity analysis and surrogate models
Bianchini A.;Papi F.;
2025
Abstract
A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high Levelized Cost of Energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor's performance and the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function, is provided by the definition of a surrogate model. An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15MW wind turbine blade optimized for specific deepwater sites in the Mediterranean Sea.
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