Presentation of the problem and objective of the experiment

The improvement in the performance characteristics of wind turbines is a challenging task, and the need for optimum designs is significantly growing. Computational Fluid Dynamics (CFD) turns out to be a unique tool enabling the optimization of wind turbines during a detailed analysis of the rotors’ blades shape and the tower design aiming to improve the overall efficiency of the structure. The consortium will utilize High Fidelity numerical models in order to assess and accurately simulate the aerodynamic performance of small wind turbines under various operational scenarios. 

Organisations involved

End User:  EUNICE Wind S.A.Domain Expert: FEAC Engineering P.C.HPC Expert: Yotta Advanced Computing Company

Short description of the experiment

In the frame of the Fortissimo call, FEAC will take advantage of the High-Performance Computing (HPC) infrastructure with the purpose to predict the aerodynamic performance of the wind turbines and provide accurate results in a reduced time. Based on EUNICE’s needs, the development of an accurate numerical model aims at the optimization of the wind turbine’s operational performance and the reduction of the periodic pressure including noise emitted by the blade-tower interaction. As a result, high fidelity simulations will provide a better understanding of the dynamic loads resulting in a manufacturing cost reduction and an energy performance increase of the final product.

Outlook

In an extraordinary display of collaborative innovation and technical prowess, the project partners assembled a sophisticated suite of Computational Fluid Dynamics (CFD) simulation models, powered by High-Performance Computing (HPC) resources. This strategic assembly was designed with a key objective: to rigorously assess and optimise wind turbine performance, with particular attention to the real-world operational conditions that the turbine would face on site.

The computational demands of this endeavour were considerable. The simulations required, on average, over 485,000 CPU hours, illustrating the computational intensity and the level of detail necessary to model such complex phenomena accurately. In total, more than 125,000 CPU hours were allocated to this project, a statistic that further highlights the complexity and precise nature of the simulations conducted.

Equally as vital as computational power was the necessity for real-world accuracy and the strict adherence to the turbine manufacturer’s guidelines. The partners meticulously observed these requirements throughout the project, ensuring that the data derived on the turbine’s operational performance under various wind conditions was both precise and manufacturer-compliant.

Adding further depth and complexity to the simulations, satellite data was employed to model the specific terrain and elevation changes at the turbine’s location. This integration of real-world topographical data into the simulation process resulted in an unprecedented level of environmental fidelity, thereby greatly enhancing the accuracy of the resultant simulations.

The simulation process itself was an intricate endeavour, reflective of the inherent complexities of wind turbine aerodynamics. Dense computational meshes, comprising of more than 50 million cells, were used. To ensure the precision of the simulations in rapidly changing conditions, a reduced time step approach was employed. Additionally, the implementation of the Detached Eddy Simulation method facilitated the modelling of complex physical phenomena, contributing significantly to the overall accuracy of the simulations.

This comprehensive simulation procedure was subsequently validated using an experimental dataset, leading to a notable reduction in the uncertainty associated with the computed results. This harmonisation of real-world data, advanced simulation techniques, and rigorous validation methods embodies the robustness and dependability of the project’s outcomes. The work completed under this initiative not only augments our understanding of wind turbine performance in diverse terrains, but also sets a new benchmark for future research in this field..

Lessons learned

The technical achievements of the project have led to significant business benefits for all participants in the value chain, from the end-user to the HPC Centre. By developing high-fidelity numerical models based on Computational Fluid Dynamics (CFD) simulations, the project has enabled the optimization of wind turbine design, improved performance, and enhanced decision-making processes.

For end-users, such as wind turbine manufacturers and operators, the project’s outputs offer substantial benefits. The high-fidelity numerical models provide valuable insights into the aerodynamic behavior, structural integrity, and overall efficiency of wind turbines. By utilizing these models, end-users can optimize the design parameters, identify potential issues, and improve the operational characteristics of wind turbines. This results in increased energy generation, higher reliability, and reduced maintenance costs. The project’s outputs empower end-users to make informed decisions, leading to improved efficiency and competitiveness in the wind energy industry.

The benefits extend throughout the value chain. Suppliers in the wind energy sector can capitalize on the improved performance and optimized designs by providing high-quality components and materials. Service providers, including maintenance and consulting firms, can offer specialized services based on the project’s findings, further enhancing their value proposition. By leveraging the project’s outputs, service providers can deliver more accurate and effective solutions to their clients.

HPC centers, as key participants in the value chain, also reap significant benefits. Their involvement in the project has allowed them to gain expertise and knowledge in applying HPC infrastructure to wind turbine simulations. This expands their capabilities and establishes them as reliable partners in the wind energy industry. HPC centers can leverage their involvement in the project to attract more clients, offer advanced simulation services, and strengthen their position in the market.

The project’s achievements have fostered collaboration and knowledge exchange among stakeholders in the wind energy sector. Wind turbine manufacturers, researchers, and engineers can collaborate to refine the numerical models and conduct joint research projects. This collaboration not only enhances technical expertise but also drives innovation and establishes strategic partnerships. The project’s outputs have created a cohesive ecosystem in the wind energy industry, where participants work together to drive continuous improvement and growth.

Expected impact

Social

Furthermore, the implementation of the novel HPC-based methodology will have a positive social impact, as it leads to improved emerging designs and more advanced wind turbine models that contribute to environmental sustainability, and avoid unnecessary waste from non-recyclable composite materials utilized in the test turbines’ construction. Ultimately, a very important aspect is that the European Commission recognizes the wind energy as a top strategic sector and is part of “European Green Deal” which strengthens the potential benefits from this project.

Business

For EUNICE WIND SA, the material and permitting cost of constructing a new wind turbine solely for testing purposes is approximately €300,000. Replacing those tests by HPC-based CFD simulations to analyze the wind turbine’s operation in its actual location reduces costs to only 10-17% of the total expense, depending on the complexity of the HPC calculations.

With the simulations optimal settings could be determined and stresses on the blades, which are indicative of potential fatigue-related malfunctions, evaluated. Simulation results lead to potentials for reduced costs through predictive maintenance and enable faster design cycles giving to EUNICE a competitive advantage.

The simulations conducted during the experiment identified optimal blade pitch angle strategies, leading to a substantial increase in energy yield. By optimizing the turbine’s operational settings, EUNICE WIND SA can now generate higher energy output from their wind turbines. This achievement has direct financial implications, as it increases the revenue potential of each turbine and improves the overall profitability of the company’s wind energy projects.

Engineering P.C. gained valuable experience in high-fidelity simulations by utilizing large-scale HPC resources. This experience allowed the company to enhance their expertise in the field of numerical simulations and advanced computing and to expand into new markets, like the wind energy sector.

Exploitation roadmap

The project’s exploitable outputs include the following:

High-Fidelity Numerical Models: The developed high-fidelity numerical models based on Computational Fluid Dynamics (CFD) simulations are an exploitable output of the project. These models can be utilized by end-users, such as wind turbine manufacturers, engineers, and researchers, to optimize the design and performance of wind turbines. The models provide valuable insights into the aerodynamic behavior, structural integrity, and overall efficiency of wind turbines, enabling end-users to make informed decisions and improvements.

Improved Wind Turbine Performance: The end-users, including wind turbine manufacturer and operators, will benefit from the project’s outputs through improved wind turbine performance. By utilizing the high-fidelity numerical models, they can optimize the design parameters, identify potential issues, and enhance the operational characteristics of wind turbines. This leads to increased energy generation, higher reliability, and reduced maintenance costs for the end-users.

Enhanced Decision-Making for End-Users: The project’s exploitable outputs empower end-users with advanced simulation tools and data-driven insights. By utilizing the high-fidelity numerical models, end-users can make more accurate and informed decisions regarding wind turbine design, operation, and maintenance. This results in improved decision-making processes, reduced risks, and enhanced efficiency in the wind energy industry.

Value Chain Participants: The entire value chain in the wind energy industry, including suppliers, service providers, and HPC centers, can benefit from the project’s outputs. The improved wind turbine performance and optimized designs positively impact the suppliers by creating a demand for high-quality components and materials. Service providers, such as maintenance and consulting firms, can offer specialized services based on the project’s findings. HPC centers benefit from their involvement in the project by gaining expertise and knowledge in applying HPC infrastructure to wind turbine simulations, further expanding their capabilities and reputation.

Collaborative Opportunities: The project’s outputs also create collaborative opportunities among different stakeholders in the wind energy sector. Wind turbine manufacturers can collaborate with researchers and engineers to further refine the numerical models and conduct joint research projects. This collaboration fosters knowledge exchange, innovation, and the establishment of strategic partnerships, strengthening the entire value chain and promoting the growth of the wind energy industry.

Overall, the project’s exploitable outputs bring benefits to end-users by providing advanced simulation tools, improving wind turbine performance, enhancing decision-making processes, and reducing operational risks. Additionally, all participants in the value chain, from end-users to HPC centers, gain advantages such as increased market demand, specialized service offerings, and the expansion of expertise and collaboration opportunities