Abstract
Accurate modeling of existing and future renewable generation is essential for planning the European energy system. Current models often neglect or oversimplify the physics of wind farm generation. While detailed modeling is possible, it is impractical for representing the entire fleet of thousands of wind power plants.
This study addresses these challenges by implementing a generic wind farm surrogate model within Correlations in Renewable Energy Sources (CorRES) tool, capable of simulating all existing wind farms in Europe over a 40-year period with hourly resolution. The model incorporates a single turbine power curve that accounts for turbulence intensity (TI) and time varying air density, alongside other relevant parameters such as specific power and rotor diameter. The wind farm power curve and wake losses are modeled to also depend on turbulence intensity and air density, as well as other key parameters like plant installation density and the number of turbines in a farm.
A comparative analysis is conducted between previous generation simulations of CorRES and those incorporating time-varying air density and fixed turbulence intensity, differentiating between offshore and onshore wind farms. The results demonstrate that incorporating time-varying air density enhances the capture of seasonal variability, which is crucial for energy system models to effectively meet electricity demand for heating and cooling with renewable energy sources.
This study addresses these challenges by implementing a generic wind farm surrogate model within Correlations in Renewable Energy Sources (CorRES) tool, capable of simulating all existing wind farms in Europe over a 40-year period with hourly resolution. The model incorporates a single turbine power curve that accounts for turbulence intensity (TI) and time varying air density, alongside other relevant parameters such as specific power and rotor diameter. The wind farm power curve and wake losses are modeled to also depend on turbulence intensity and air density, as well as other key parameters like plant installation density and the number of turbines in a farm.
A comparative analysis is conducted between previous generation simulations of CorRES and those incorporating time-varying air density and fixed turbulence intensity, differentiating between offshore and onshore wind farms. The results demonstrate that incorporating time-varying air density enhances the capture of seasonal variability, which is crucial for energy system models to effectively meet electricity demand for heating and cooling with renewable energy sources.
Original language | English |
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Title of host publication | Proceedings of 23rd Wind & Solar Integration Workshop |
Number of pages | 7 |
Publication date | 2024 |
Publication status | Published - 2024 |
Event | 23rd Wind & Solar Integration Workshop - Helsinki, Finland Duration: 8 Oct 2024 → 11 Oct 2024 |
Workshop
Workshop | 23rd Wind & Solar Integration Workshop |
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Country/Territory | Finland |
City | Helsinki |
Period | 08/10/2024 → 11/10/2024 |
Bibliographical note
This paper was presented at the 23rd Wind & Solar Integration Workshop 2024 and published in the workshop’s proceedingsKeywords
- Wind wakes
- Energy system
- Turbulence intensity
- Air density