Review and evaluation of wake loss models for wind energy applications

•6 analytical wake loss models evaluated (3 for first time) with data from 3 wind farms.•The 3 wind farms are a combination of offshore, inland, regular, and irregular layouts.•Validation for wind directions aligned and non-aligned with the turbine rows. Choosing an appropriate wake loss model (WLM)...

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Bibliographic Details
Published in:Applied energy 2018-09, Vol.226, p.1187-1207
Main Authors: Archer, Cristina L., Vasel-Be-Hagh, Ahmadreza, Yan, Chi, Wu, Sicheng, Pan, Yang, Brodie, Joseph F., Maguire, A. Eoghan
Format: Article
Language:English
Subjects:
Analytical wake loss models
Wake losses
Wind energy
Wind farms
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Summary:•6 analytical wake loss models evaluated (3 for first time) with data from 3 wind farms.•The 3 wind farms are a combination of offshore, inland, regular, and irregular layouts.•Validation for wind directions aligned and non-aligned with the turbine rows. Choosing an appropriate wake loss model (WLM) is a critical task in predicting power production of a wind farm and performing a wind farm layout optimization. Due to their efficient computational performance, analytical WLMs, also called kinematic models, are the most likely candidates for such applications. This paper examines the performance of six well-known analytical WLMs, i.e., Jensen, Larsen, Frandsen, Bastankah and Porté-Agel (BPA), Xie and Archer (XA), and Geometric Model (GM), by comparing their absolute error, bias, correlation coefficient, and ability to predict power production within one standard deviation of the mean observed values at three major commercial wind farms: Lillgrund (offshore, in Sweden), Anholt (offshore, in Denmark) and Nørrekær (inland, in Denmark). The three wind farms are chosen to cover many aspects of wind farms, such as offshore and inland conditions, regular and irregular layouts, and closely- to widely-spaced turbines. The conclusions of this review and the recommendations that are put forward provide practical guidelines for using analytical WLMs effectively in future wind energy applications. Overall, the Jensen and XA models stand out for their consistently strong performance and for rarely (Jensen) or never (XA) ranking last for all wind directions at all farms and are therefore the recommended models in general.
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2018.05.085