Far Wake Model Implementation into the Three-Dimensional Dynamic Wind Farm Simulation Model SWiPLab-WFM

This paper presents first results and validation aspects of the implementation of far wake behavior into the Smart WindPark Laboratory Wind Flow Model in order to predict the impact of wind turbines on downwind wind farms through their wakes. Due to cluster formation, especially offshore, wind farms are located relatively close to each other, resulting in complex aerodynamic couplings which depend on wind direction, wind speed, ambient turbulence and atmospheric stability as well as wind turbine operation. This leads not only to decreased wind speeds behind wind farms and consequently reduced power conversion of waked wind farms, but also to increased fatigue loads, both lowering return on investment. Simulation results obtained with the modified simulation model are presented in the paper and compared to measurement data from literature.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905273
Citations
2
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
2.60
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article

Far Wake Model Implementation into the Three-Dimensional Dynamic Wind Farm Simulation Model SWiPLab-WFM

Constantinos Sourkounis, Vile Kipke, Paul Rowsell
2 citations
Wind Energy Research and Development
2.60
article

Far Wake Model Implementation into the Three-Dimensional Dynamic Wind Farm Simulation Model SWiPLab-WFM

Constantinos Sourkounis, Vile Kipke, Paul Rowsell
article en
2 citations

Abstract

This paper presents first results and validation aspects of the implementation of far wake behavior into the Smart WindPark Laboratory Wind Flow Model in order to predict the impact of wind turbines on downwind wind farms through their wakes. Due to cluster formation, especially offshore, wind farms are located relatively close to each other, resulting in complex aerodynamic couplings which depend on wind direction, wind speed, ambient turbulence and atmospheric stability as well as wind turbine operation. This leads not only to decreased wind speeds behind wind farms and consequently reduced power conversion of waked wind farms, but also to increased fatigue loads, both lowering return on investment. Simulation results obtained with the modified simulation model are presented in the paper and compared to measurement data from literature.

Ruhr University Bochum (DE)
Affordable and clean energy
Openalex Percentile: Top 7%
Wind Energy Research and Development
2.60
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