P. Veers, C. Bottasso, L. Manuel, J. Naughton, L. Pao, J. Paquette, A. Robertson, M. Robinson, S. Ananthan, T. Barlas, A. Bianchini, Henrik Bredmose, S. G. Horcas, J. Keller, H. A. Madsen, J. Manwell, P. Moriarty, S. Nolet, J. Rinker
{"title":"Grand challenges in the design, manufacture, and operation of future wind turbine systems","authors":"P. Veers, C. Bottasso, L. Manuel, J. Naughton, L. Pao, J. Paquette, A. Robertson, M. Robinson, S. Ananthan, T. Barlas, A. Bianchini, Henrik Bredmose, S. G. Horcas, J. Keller, H. A. Madsen, J. Manwell, P. Moriarty, S. Nolet, J. Rinker","doi":"10.5194/wes-8-1071-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are\narticulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push\nthe frontiers in the design of turbine and plant systems. Modern turbine\nrotors operate through the entire atmospheric boundary layer, outside the\nbounds of historic design assumptions, which requires reassessing design\nprocesses and approaches. Traditional aerodynamics and aeroelastic modeling\napproaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load\nalleviation potential. Opportunities in co-design can bring controls\nupstream into design optimization if captured in design-level models of the\nphysical phenomena. It is a research challenge to integrate improved\nmaterials into the manufacture of ever-larger components while maintaining\nquality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions\nneeded to continue the progress of wind energy technology toward even lower\ncost and greater functionality are recommended.\n","PeriodicalId":46540,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wind Energy Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/wes-8-1071-2023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 13
Abstract
Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are
articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push
the frontiers in the design of turbine and plant systems. Modern turbine
rotors operate through the entire atmospheric boundary layer, outside the
bounds of historic design assumptions, which requires reassessing design
processes and approaches. Traditional aerodynamics and aeroelastic modeling
approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load
alleviation potential. Opportunities in co-design can bring controls
upstream into design optimization if captured in design-level models of the
physical phenomena. It is a research challenge to integrate improved
materials into the manufacture of ever-larger components while maintaining
quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions
needed to continue the progress of wind energy technology toward even lower
cost and greater functionality are recommended.