An alternative form of the super-Gaussian wind turbine wake model

Author:

Blondel Frédéric,Cathelain Marie

Abstract

Abstract. A new analytical wind turbine wake model, based on a super-Gaussian shape function, is presented. The super-Gaussian function evolves from a nearly top-hat shape in the near wake to a Gaussian shape in the far wake, which is consistent with observations and measurements of wind turbine wakes. Using such a shape function allows the recovery of the mass and momentum conservation that is violated when applying a near-wake regularization function to the expression of the maximum velocity deficit of the Gaussian wake model. After a brief introduction of the theoretical aspects, an easy-to-implement model with a limited number of parameters is derived. The super-Gaussian model predictions are compared to wind tunnel measurements, full-scale measurements, and a large-eddy simulation (LES), showing a good agreement and an improvement compared with predictions based on the Gaussian model.

Publisher

Copernicus GmbH

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference23 articles.

1. Aubrun, S., Loyer, S., Hancock, P., and Hayden, P.: Wind turbine wake properties: Comparison between a non-rotating simplified wind turbine model and a rotating model, J. Wind Eng. Ind. Aerod., 120, 1–8, https://doi.org/10.1016/j.jweia.2013.06.007, 2013. a, b, c, d

2. Bartl, J. and Sætran, L.: Blind test comparison of the performance and wake flow between two in-line wind turbines exposed to different turbulent inflow conditions, Wind Energ. Sci., 2, 55–76, https://doi.org/10.5194/wes-2-55-2017, 2017. a

3. Bastankhah, M. and Porté-Agel, F.: A new analytical model for wind-turbine wakes, Renew. Energ., 70, 116–123, https://doi.org/10.1016/j.renene.2014.01.002, 2014. a, b, c, d, e, f, g

4. Bastankhah, M. and Porté-Agel, F.: Experimental and theoretical study of wind turbine wakes in yawed conditions, Zenodo, https://doi.org/10.5281/zenodo.3607598, 2020. a

5. Boorsma, K., Schepers, J., Gomez-Iradi, S., Herraez, I., Lutz, T., Weihing, P., Oggiano, L., Pirrung, G., Madsen, H., Shen, W., Rahimi, H., and Schaffarczyk, P.: Final Report of IEA Wind Task 29 Mexnext (Phase 3), Tech. Rep. ECN-E–18-003, ECN Wind Energy, available at: https://publications.ecn.nl/WIN/0/ECN-E--18-003, last access: 18 November 2019. a

Cited by 48 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3