Neighborhood effects in wind farm performance: An econometric approach

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: SFB 649 Discussion Paper ; No. 2016-012

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Alternative Energy Sources ; Energy Forecasting
• Thema: wind energy ; wake modeling ; wind farm design

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Ritter, Matthias ; Pieralli, Simone ; Odening, Martin
• Ereignis: Veröffentlichung
• (wer): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (wo): Berlin
• (wann): 2016

Weitere Informationen

• Handle: http://hdl.handle.net/10419/146181
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ