A novel superposition method for streamwise turbulence intensity of wind-turbine wakes

Li Li, Bing Wang, Mingwei Ge, Zhi Huang, Xintao Li and Yongqian Liu

Energy, 2023, vol. 276, issue C

Abstract: The prediction of the streamwise turbulence intensity distribution in a wind farm is of great significance for wind turbine micrositing. However, most studies only focus on the superposition methods of velocity deficit in turbine wakes, and high-precision superposition models for turbulence intensity are still lacking. To address this issue, wakes of a column of aligned wind turbines with different ground roughness heights are studied via high-fidelity large-eddy simulation. It is found that the variation of added streamwise turbulence intensity with streamwise direction is very similar to that of velocity deficit; however, there are distinct differences regarding recovery rate and incidence. Four common superposition methods extended from wake velocity are examined for turbulence intensity, and they all fail to accurately predict the superposition effect of turbulence intensity. To remedy this, a normalized superposition formula of turbulence intensity is proposed. In this formula, the parameter can be adjusted to alter the superposition ratio for downstream turbines, and it can encompass existing common superposition models. Both large-eddy simulations and wind tunnel experiments demonstrate that the 2.5 times superposition (model parameter = 2.5) method can accurately predict the distribution of streamwise turbulence intensity for aligned turbines, providing superior prediction accuracy compared to existing models.

Keywords: Wind-turbine wake; Added streamwise turbulence intensity; Large-eddy simulation; Superposition model (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422300885X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:276:y:2023:i:c:s036054422300885x

DOI: 10.1016/j.energy.2023.127491

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().