2017
DOI: 10.3390/en10030365
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Neighborhood Effects in Wind Farm Performance: A Regression Approach

Abstract: Abstract:The optimization of turbine density in wind farms entails a trade-off between the usage of scarce, expensive land and power losses through turbine wake effects. A quantification and prediction of the wake effect, however, is challenging because of the complex aerodynamic nature of the interdependencies of turbines. In this paper, we propose a parsimonious data driven regression wake model that can be used to predict production losses of existing and potential wind farms. Motivated by simple engineerin… Show more

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Cited by 6 publications
(5 citation statements)
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“…However, wind farm wake effects were ignored. A quantification and prediction of the wake effect losses is challenging because of the complex aerodynamic nature of the interdependencies of turbines [40] and therefore deserves greater attention in future studies. Atmospheric stability also plays a significant role in the accuracy of wind speed extrapolation.…”
Section: Discussionmentioning
confidence: 99%
“…However, wind farm wake effects were ignored. A quantification and prediction of the wake effect losses is challenging because of the complex aerodynamic nature of the interdependencies of turbines [40] and therefore deserves greater attention in future studies. Atmospheric stability also plays a significant role in the accuracy of wind speed extrapolation.…”
Section: Discussionmentioning
confidence: 99%
“…This number can be increased by installing more or larger turbines or photovoltaic systems on the roof of a residential building. For a high density of turbines, however, shadowing effects would have to be considered [29]. Finally, we want to compare the potential of wind and solar energy with the average electricity consumption of a household in Gaza.…”
Section: Resultsmentioning
confidence: 99%
“…This number can be increased by installing more or larger turbines or photovoltaic systems on the roof of a residential building. For a high density of turbines, however, shadowing effects would have to be considered [29].…”
Section: Resultsmentioning
confidence: 99%
“…However, other studies had suggested that, as part of pre-construction assessment, plausible models could guide the siting of individual high-risk turbines to adjacent areas [74] with minimal impact on the overall wind farm performance. Alternatively, the optimization of turbine density [75] in locations that exhibited a high potential for wind energy development and a low-risk of collision, could also reduce the impact of the production losses, which were as a result of the conservation of high potential but high-risk corridors. Additionally, the models of the kind that were specified in this study could have also facilitated post-construction mitigation by highlighting the individual high-risk turbines that could be shut off temporarily in periods when there was a high frequency of birds near the wind farms.…”
Section: Limitations and Future Research Directionsmentioning
confidence: 99%