Investigation of fully coupled wind field simulations in complex terrain wind farms considering automatic upwind control of turbines
Shuanglong Fan and
Zhenqing Liu
Renewable Energy, 2025, vol. 239, issue C
Abstract:
The investigation of the wake characteristics of wind turbines in complex topography is essential for optimizing wind energy utilization. This paper presents a fully-coupled simulation method, the Actuator Disk Model with Dynamic Rotation (ADM-DR), for simulating wake flow in wind farms with real terrain. This method integrates automatic upwind and speed control of turbines and utilizes a multi-level grid encryption mode. Its application in wind farms with real terrain is studied in detail and compared with the traditional model, ADM-R (Actuator Disk Model with Rotation). It was observed that for a single wind turbine, the results of the two models regarding wind speed distribution in the wake zone exhibited negligible differences. However, in clustered wind turbine arrangements, the fully-coupled model demonstrated superior applicability compared to the traditional model. It provided more accurate predictions of wake characteristics and the power output of turbines in the rear row. Furthermore, the ADM-DR model's power forecast results were about 15.6 % greater compared to those of the ADM-R model. This underscores the crucial role of accounting for the automatic upwind alignment of wind turbines to accurately evaluate energy production when assessing wind resources for prospective wind farms.
Keywords: Complex topography; Wind turbine wake; Automatic upwind; Large eddy simulation (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148124022146
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:renene:v:239:y:2025:i:c:s0960148124022146
DOI: 10.1016/j.renene.2024.122146
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().