Unlocking the Complexities of Wind Farm-Atmosphere Interaction: A Multi-Scale Approach
This project aims to enhance wind farm performance forecasts by using high-resolution 3D simulations to study the dynamic interactions between wind farms, weather, ocean, and clouds.
Projectdetails
Introduction
Turbulence drives transport processes in the atmosphere and determines Earth’s weather and climate. Wind farm performance depends on atmospheric turbulence as it entrains energy into wind turbine arrays.
Challenges in Current Simulations
As wind turbines and farms expand in size, they increasingly interact with an unexplored atmospheric region and large-scale weather phenomena in ways that are not fully understood. Typical wind farm simulations assume idealized cases and do not capture the influence of:
- Dynamic changes in atmospheric conditions
- The interaction between the atmosphere and ocean
- The influence of clouds
In reality, these effects are dynamic and influence atmospheric turbulent flow across a wind farm. Understanding these interactions is crucial to optimize wind farm design, control, and power production forecasts.
Impact on Large-Scale Processes
Far beyond the local scale, wind farm physics impact large-scale atmospheric processes. Outstanding questions include how wind farms influence:
- Large-scale weather phenomena
- Atmospheric stability
- Moisture dispersion
- Clouds
The influence of wind farms on heat and momentum exchange between the atmosphere and ocean is also not fully understood.
Proposed Approach
To bridge these knowledge gaps, I envision using 3D simulations to locally model the wind farm flow physics (microscale) in a weather model (mesoscale). This is a conceptually different approach from typical weather models that use a limited refinement of microscale processes throughout the domain.
Goals and Techniques
Using high-resolution simulations, I will go beyond idealized cases and explore dynamic interaction between the atmosphere, ocean, clouds, and wind farms. The goal is to study wind farm interaction with realistic weather conditions and provide more accurate wind production forecasts.
I will develop novel computational techniques to increase the domain size of high-resolution simulations. Addressing these fundamental modeling challenges is crucial to unlock the complex interaction between wind farms and the atmosphere.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.000.000 |
Totale projectbegroting | € 2.000.000 |
Tijdlijn
Startdatum | 1-5-2024 |
Einddatum | 30-4-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- UNIVERSITEIT TWENTEpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Data-Driven Approaches in Computational Mechanics for the Aerohydroelastic Analysis of Offshore Wind TurbinesDATA-DRIVEN OFFSHORE aims to enhance offshore wind turbine design by integrating experimental data into aerohydroelastic simulations, improving predictive capabilities and enabling efficient upscaling beyond 20 MW. | ERC Consolid... | € 2.000.000 | 2023 | Details |
Beyond self-similarity in turbulenceThis project aims to develop and validate a theory for intermediate-strain turbulence using machine learning and advanced simulations to enhance engineering applications like wind energy and UAV efficiency. | ERC Starting... | € 1.498.820 | 2025 | Details |
Unraveling the impact of turbulence in Mixed-phase CloudsThe MixClouds project aims to analyze the impact of turbulence on mixed-phase clouds' microphysics using theoretical and numerical tools to enhance understanding and modeling of atmospheric processes. | ERC Consolid... | € 1.998.531 | 2024 | Details |
Open Superior Efficient Solar Atmosphere Model ExtensionDevelop a high-order GPU-enabled 3D time-evolving multi-fluid model of the solar atmosphere to enhance understanding of solar wind, flares, and CMEs for improved Earth impact predictions. | ERC Advanced... | € 2.498.230 | 2024 | Details |
Small Flows with Big Consequences: Wave-, Turbulence- and Shear current-Driven mixing under a water surfaceWaTurSheD aims to empirically model the mixing of surface waves, turbulence, and shear currents in the ocean to improve climate simulations by developing a universal scaling law for WTS flows. | ERC Consolid... | € 1.958.705 | 2023 | Details |
Data-Driven Approaches in Computational Mechanics for the Aerohydroelastic Analysis of Offshore Wind Turbines
DATA-DRIVEN OFFSHORE aims to enhance offshore wind turbine design by integrating experimental data into aerohydroelastic simulations, improving predictive capabilities and enabling efficient upscaling beyond 20 MW.
Beyond self-similarity in turbulence
This project aims to develop and validate a theory for intermediate-strain turbulence using machine learning and advanced simulations to enhance engineering applications like wind energy and UAV efficiency.
Unraveling the impact of turbulence in Mixed-phase Clouds
The MixClouds project aims to analyze the impact of turbulence on mixed-phase clouds' microphysics using theoretical and numerical tools to enhance understanding and modeling of atmospheric processes.
Open Superior Efficient Solar Atmosphere Model Extension
Develop a high-order GPU-enabled 3D time-evolving multi-fluid model of the solar atmosphere to enhance understanding of solar wind, flares, and CMEs for improved Earth impact predictions.
Small Flows with Big Consequences: Wave-, Turbulence- and Shear current-Driven mixing under a water surface
WaTurSheD aims to empirically model the mixing of surface waves, turbulence, and shear currents in the ocean to improve climate simulations by developing a universal scaling law for WTS flows.
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