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Neighborhood Effects in Wind Farm Performance: An Econometric Approach
Humboldt-Universität zu Berlin, Germany.ORCID iD: 0000-0003-2543-3673
Humboldt-Universität zu Berlin, Germany.
Humboldt-Universität zu Berlin, Germany.
2016 (English)Report (Other academic)
Abstract [en]

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 econometric wake model that can be used to predict production losses of existing and potential wind parks. Motivated by simple engineering wake models, the predicting variables are wind speed, turbine alignment angle, and distance. By utilizing data from two wind parks in Germany, a significantly better prediction of wake effect losses is attained compared to the standard Jensen model. A scenario analysis reveals that a distance between turbines can be reduced up to three times the rotor size without entailing substantial production losses. In contrast, a suboptimal configuration of turbines with respect to the main wind direction can result in production losses that are five times higher.

Place, publisher, year, edition, pages
Berlin: Humboldt-Universität zu Berlin , 2016. , p. 16
Series
SFB 649 Discussion Paper, ISSN 1860-5664 ; 2016-012
Keywords [en]
Wind energy; wake modeling; wind farm design
National Category
Economics
Identifiers
URN: urn:nbn:se:hj:diva-55236OAI: oai:DiVA.org:hj-55236DiVA, id: diva2:1616833
Available from: 2021-12-04 Created: 2021-12-04 Last updated: 2021-12-04Bibliographically approved

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Ritter, Matthias

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