HORIZON EUROPE
Expected Outcome:As wind turbines grow bigger and taller, the blade tips are increasing more affected by turbulent atmospheric flow features, while airborne wind energy systems operate at even higher altitudes. This zone of the atmosphere currently lays between the current numeric models at the microscale and the mesoscale. Further, the data integration of the models of these different altitudes is still scarce. Thus, there is a need for an improved understanding of atmospheric flow physics, particularly regarding wind power production forecasting and the design of wind energy technology components.
It is expected that better predictions of wind patterns should:
Support improved wind farm design, location choice, distribution and operation thus bridging the gap between small-scale controlled experiments and full-scale deployment;Enhance system reliability and power production;Decrease economic uncertainties related to farm design and power production, as well as wind technology components design and durability;Lead to the development of numerical models capable of accurately forecasting high wind flow and power production. It will also improve wakes model...
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Expected Outcome:As wind turbines grow bigger and taller, the blade tips are increasing more affected by turbulent atmospheric flow features, while airborne wind energy systems operate at even higher altitudes. This zone of the atmosphere currently lays between the current numeric models at the microscale and the mesoscale. Further, the data integration of the models of these different altitudes is still scarce. Thus, there is a need for an improved understanding of atmospheric flow physics, particularly regarding wind power production forecasting and the design of wind energy technology components.
It is expected that better predictions of wind patterns should:
Support improved wind farm design, location choice, distribution and operation thus bridging the gap between small-scale controlled experiments and full-scale deployment;Enhance system reliability and power production;Decrease economic uncertainties related to farm design and power production, as well as wind technology components design and durability;Lead to the development of numerical models capable of accurately forecasting high wind flow and power production. It will also improve wakes modelling and the integration of models with real condition wind farm data;Use open access of Big Data storage and usage for the testing and performance tracking of the numeric models. Scope:The proposal is expected to address all of the following aspects:
Develop an open access knowledge hub for experimental data, based on the principles of open data sharing. Develop and validate numeric models to accurately forecast wind flow in low, medium and high altitudes in onshore and offshore scenarios. These models should address how external factors, such as wind conditions, and different climate affect power production and loads on target and neighbouring wind power systems;Integrate these different developments (knowledge hub and forecasting models) into a tool able to be readily absorbed by the sector. This integrated approach need to be applicable to at least 2 of these different wind energy conversion technologies: onshore wind, offshore wind (fixed bottom or floating), and high altitude wind systems;Validate and promote how such tools could be used to improve the design and deployment of wind farms, through case studies;Address and test how such integrated tools can be used for design development of wind technology components (for example blades, towers, substructures, kites, etc.), in particular on the issue of energy efficiency and material durability. Further indirect impacts on decreased material usage, system efficiency, and social issues should also be made explicit. In order to optimise impact and enhance synergies, cooperation with projects from the Horizon 2020 LC-SC3-RES-31-2020 call is particularly encouraged.
Synergies are possible with topic: HORIZON-CL4-DIGITAL-EMERGING-2022-01-18: 2D materials-based devices and systems for energy storage and/or harvesting (RIA).
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