Review and evaluation of wake loss models for wind energy applications

Cristina L. Archer, Ahmadreza Vasel-Be-Hagh, Chi Yan, Sicheng Wu, Yang Pan, Joseph F. Brodie and A. Eoghan Maguire

Applied Energy, 2018, vol. 226, issue C, 1187-1207

Abstract: 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.

Keywords: Wake losses; Analytical wake loss models; Wind energy; Wind farms (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (59)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:226:y:2018:i:c:p:1187-1207

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DOI: 10.1016/j.apenergy.2018.05.085

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