On the load impact of dynamic wind farm wake mixing strategies

Joeri A. Frederik and Jan-Willem van Wingerden

Renewable Energy, 2022, vol. 194, issue C, 582-595

Abstract: In recent studies, the effectiveness of different so-called wake mixing strategies has been assessed in terms of wind farm power maximization. These studies show that by dynamically varying the pitch angles of a wind turbine, wake mixing can be enhanced to increase the overall power production of a wind farm. However, such strategies also increase the loads experienced by the turbine, which may disqualify such methods as viable wind farm control strategies. In this paper, an extensive analysis of the load effects of two specific wake mixing strategies, Dynamic Induction Control (DIC) and the helix approach, is presented. The damage equivalent load of critical components such as the turbine blades and tower is assessed, and the risk of fatigue damage on the blade pitch bearings is determined. This paper therefore contributes to determining the implementability of such wake mixing strategies in wind farms of the future.

Keywords: Dynamic wake mixing; Wind farm control; Damage equivalent load; Blade bearing damage; Dynamic induction control; Individual pitch control; Helix approach (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148122007613
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:194:y:2022:i:c:p:582-595

DOI: 10.1016/j.renene.2022.05.110

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 ().