A new analytical model for wind-turbine wakes

Bastankhah, Majid; Porté-Agel, Fernando

Abstract

A new analytical wake model is proposed and validated to predict the wind velocity distribution downwind of a wind turbine. The model is derived by applying conservation of mass and momentum and assuming a Gaussian distribution for the velocity de fi cit in the wake. This simple model only requires one parameter to determine the velocity distribution in the wake. The results are compared to high- resolution wind-tunnel measurements and large-eddy simulation (LES) data of miniature wind- turbine wakes, as well as LES data of real-scale wind-turbine wakes. In general, it is found that the velocity de fi cit in the wake predicted by the proposed analytical model is in good agreement with the experimental and LES data. The results also show that the new model predicts the power extracted by downwind wind turbines more accurately than other common analytical models, some of which are based on less accurate assumptions like considering a top-hat shape for the velocity de fi cit.

Citation

Bastankhah, M., & Porté-Agel, F. (2014). A new analytical model for wind-turbine wakes. Renewable Energy, 70, 116-123. https://doi.org/10.1016/j.renene.2014.01.002

• Journal Article Type: Article
• Acceptance Date: Jan 4, 2014
• Online Publication Date: Jan 31, 2014
• Publication Date: 2014-10
• Deposit Date: Nov 20, 2018
• Journal: Renewable Energy
• Print ISSN: 0960-1481
• Electronic ISSN: 1879-0682
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 70
• Pages: 116-123
• DOI: https://doi.org/10.1016/j.renene.2014.01.002
• Public URL: https://durham-repository.worktribe.com/output/1313906