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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 (engelsk)Rapport (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Berlin: Humboldt-Universität zu Berlin , 2016. , s. 16
Serie
SFB 649 Discussion Paper, ISSN 1860-5664 ; 2016-012
Emneord [en]
Wind energy; wake modeling; wind farm design
HSV kategori
Identifikatorer
URN: urn:nbn:se:hj:diva-55236OAI: oai:DiVA.org:hj-55236DiVA, id: diva2:1616833
Tilgjengelig fra: 2021-12-04 Laget: 2021-12-04 Sist oppdatert: 2021-12-04bibliografisk kontrollert

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