Aerodynamic Design of Wind Turbine Blades Using Multi-Fidelity Analysis and Surrogate Models

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, 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 (SM). 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 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea.

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Publication Details

Journal
International Journal of Turbomachinery Propulsion and Power
Published
2025-07-16
DOI
https://doi.org/10.3390/ijtpp10030016
Citations
2
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
9.99
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article

Aerodynamic Design of Wind Turbine Blades Using Multi-Fidelity Analysis and Surrogate Models

Franco Rispoli, Alessandro Corsini, Alessandro Bianchini, Riccardo Broglia et al.
2 citations
International Journal of Turbomachinery Propulsion and Power
Wind Energy Research and Development
9.99
article

Aerodynamic Design of Wind Turbine Blades Using Multi-Fidelity Analysis and Surrogate Models

Franco Rispoli, Alessandro Corsini, Alessandro Bianchini, Riccardo Broglia, Alessio Castorrini, Francesco Papi, Rosalba Cardamone
article en
2 citations

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, 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 (SM). 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 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea.

International Journal of Turbomachinery Propulsion and PowerVol. 10(3)
Institute of Marine Engineering (IT), University of Florence (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 3%
Wind Energy Research and Development
9.99
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