Articles | Volume 6, issue 6
https://doi.org/10.5194/wes-6-1455-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-6-1455-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Nov 2021
Research article |
| 15 Nov 2021
| 15 Nov 2021
On the effects of inter-farm interactions at the offshore wind farm Alpha Ventus
Vasilis Pettas
CORRESPONDING AUTHOR
Stuttgart Wind Energy (SWE), University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Matthias Kretschmer
Stuttgart Wind Energy (SWE), University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Andrew Clifton
Stuttgart Wind Energy (SWE), University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Po Wen Cheng
Stuttgart Wind Energy (SWE), University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
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Cited
20 citations as recorded by crossref.
- Inter-farm wake effect on layout optimization: Case study of standardized two-phase wind farms K. Yang et al. 10.1016/j.awe.2024.100021
- Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights X. Xu et al. 10.1007/s13344-023-0009-3
- A Comparative Study on Load Assessment Methods for Offshore Wind Turbines Using a Simplified Method and OpenFAST Simulations S. Jawalageri et al. 10.3390/en17092189
- Innovative aerodynamic rotor concept for demand-oriented power feed-in of offshore wind turbines D. Ribnitzky et al. 10.1088/1742-6596/2265/3/032017
- Strain virtual sensor for offshore wind turbine jacket supports: A time series transformer approach validated with Alpha Ventus wind farm data Á. Encalada-Dávila et al. 10.1016/j.ymssp.2025.112653
- Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes Z. Li et al. 10.3390/en15186533
- Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms G. Kütükçü & O. Uzol 10.1063/5.0107244
- Damage Detection and Localization at the Jacket Support of an Offshore Wind Turbine Using Transformer Models H. Triviño et al. 10.1155/2023/6646599
- Impacts of offshore wind farms in the English Channel on larval dispersal and connectivity of benthic species using numerical modeling S. Ajmi et al. 10.1007/s10236-025-01665-8
- Gone with the wind? Wind farm-induced wakes and regulatory gaps E. Finserås et al. 10.1016/j.marpol.2023.105897
- Comparison of near wind farm wake measurements from scanning lidar with engineering models A. Anantharaman et al. 10.1088/1742-6596/2265/2/022034
- Hybrid-Lambda: a low-specific-rating rotor concept for offshore wind turbines D. Ribnitzky et al. 10.5194/wes-9-359-2024
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- The future of offshore wind power production: Wake and climate impacts S. Warder & M. Piggott 10.1016/j.apenergy.2024.124956
- Wind-farm power prediction using a turbulence-optimized Gaussian wake model N. Zehtabiyan-Rezaie et al. 10.1016/j.weer.2024.100007
- A passively self-adjusting floating wind farm layout to increase the energy production: a sensitivity analysis M. Mahfouz & P. Cheng 10.1088/1742-6596/2626/1/012053
- Investigation of wake steering control effects on the dynamic responses of 15 MW semi-submersible floating wind farms T. Zhang et al. 10.1016/j.renene.2025.123704
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. 10.5194/essd-16-4777-2024
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
- FAST.Farm load validation for single wake situations at alpha ventus M. Kretschmer et al. 10.5194/wes-6-1247-2021
19 citations as recorded by crossref.
- Inter-farm wake effect on layout optimization: Case study of standardized two-phase wind farms K. Yang et al. 10.1016/j.awe.2024.100021
- Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights X. Xu et al. 10.1007/s13344-023-0009-3
- A Comparative Study on Load Assessment Methods for Offshore Wind Turbines Using a Simplified Method and OpenFAST Simulations S. Jawalageri et al. 10.3390/en17092189
- Innovative aerodynamic rotor concept for demand-oriented power feed-in of offshore wind turbines D. Ribnitzky et al. 10.1088/1742-6596/2265/3/032017
- Strain virtual sensor for offshore wind turbine jacket supports: A time series transformer approach validated with Alpha Ventus wind farm data Á. Encalada-Dávila et al. 10.1016/j.ymssp.2025.112653
- Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes Z. Li et al. 10.3390/en15186533
- Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms G. Kütükçü & O. Uzol 10.1063/5.0107244
- Damage Detection and Localization at the Jacket Support of an Offshore Wind Turbine Using Transformer Models H. Triviño et al. 10.1155/2023/6646599
- Impacts of offshore wind farms in the English Channel on larval dispersal and connectivity of benthic species using numerical modeling S. Ajmi et al. 10.1007/s10236-025-01665-8
- Gone with the wind? Wind farm-induced wakes and regulatory gaps E. Finserås et al. 10.1016/j.marpol.2023.105897
- Comparison of near wind farm wake measurements from scanning lidar with engineering models A. Anantharaman et al. 10.1088/1742-6596/2265/2/022034
- Hybrid-Lambda: a low-specific-rating rotor concept for offshore wind turbines D. Ribnitzky et al. 10.5194/wes-9-359-2024
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. 10.5194/wes-9-1507-2024
- The future of offshore wind power production: Wake and climate impacts S. Warder & M. Piggott 10.1016/j.apenergy.2024.124956
- Wind-farm power prediction using a turbulence-optimized Gaussian wake model N. Zehtabiyan-Rezaie et al. 10.1016/j.weer.2024.100007
- A passively self-adjusting floating wind farm layout to increase the energy production: a sensitivity analysis M. Mahfouz & P. Cheng 10.1088/1742-6596/2626/1/012053
- Investigation of wake steering control effects on the dynamic responses of 15 MW semi-submersible floating wind farms T. Zhang et al. 10.1016/j.renene.2025.123704
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. 10.5194/essd-16-4777-2024
- Modular deep learning approach for wind farm power forecasting and wake loss prediction S. Ally et al. 10.5194/wes-10-779-2025
1 citations as recorded by crossref.
Latest update: 24 Jun 2025
Short summary
This study aims to quantify the effect of inter-farm interactions based on long-term measurement data from the Alpha Ventus (AV) wind farm and the nearby FINO1 platform. AV was initially the only operating farm in the area, but in subsequent years several farms were built around it. This setup allows us to quantify the farm wake effects on the microclimate of AV and also on turbine loads and operational characteristics depending on the distance and size of the neighboring farms.
This study aims to quantify the effect of inter-farm interactions based on long-term measurement...
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