A multiscale numerical framework coupled with control strategies for simulating a wind farm in complex terrain

Qiang Wang, Kun Luo, Renyu Yuan, Shuai Wang, Jianren Fan and Kefa Cen

Energy, 2020, vol. 203, issue C

Abstract: Improving the accuracy of the evaluation on the performance of wind farms in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power. To this end, a multiscale numerical framework (MNF) integrating the WRF model coupled with a wind farm parameterization and a LES model embedded with the wind turbine control strategies is developed. An interface for data exchange between the WRF and LES models is established. The simulated nacelle velocity and the generator power results agree well with the observations, proving that the MNF is capable of assessing the flow behavior and performance of a realistic onshore wind farm in complex terrain. Besides, the impacts of terrain on the operating process for wind turbines over the hill under the dynamic inflow condition are quantified. The results show that the wind turbine at the top of the hill can cut in the rated-state earlier and cut out later, which improves the power output by 5.5%, indicating that the total generation of wind farms can be enhanced by making full use of terrain acceleration. This high-fidelity multiscale numerical framework is expected to be an effective tool for the siting and optimization of wind farms.

Keywords: Wind farm; Complex terrain; Multiscale numerical framework; Control strategy; Operating process (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220310203
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:203:y:2020:i:c:s0360544220310203

DOI: 10.1016/j.energy.2020.117913

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 ().