Model-free control of wind farms: A comparative study between individual and coordinated extremum seeking

Umberto Ciri, Mario A. Rotea and Stefano Leonardi

Renewable Energy, 2017, vol. 113, issue C, 1033-1045

Abstract: Large Eddy Simulations of the turbulent flow over an array of wind turbines have been performed to evaluate a model-free approach to power optimization. Two different implementations have been tested: (i) individual extremum-seeking control (IESC), which optimizes the power of the single turbines individually; (ii) nested ESC (NESC), which coordinates the single controllers to seek a farm-level optimum. Both schemes provide a gain over the baseline, which operates all the turbines with ideal design set-points. These settings are found to be sub-optimal for waked turbines. The NESC provides a slightly larger power production than the independent ESC, albeit it has a slower convergence to the optimum. Therefore, depending on wind variability, both strategies may be employed. IESC is more appropriate for sites with wind conditions changing on a short time scale, while NESC should be preferred when the wind conditions are quite stable. Since the extremum-seeking algorithm is model-free, uncertainties in atmospheric conditions, aging of the turbine or numerical dissipation due to the sub-grid model should not change the general conclusions reached in this paper. This methodology can provide reliable results and permits to gain, through the analysis, a useful knowledge on the mechanisms leading to the performance enhancement.

Keywords: Wind farm control; Optimization; Extremum seeking control; Dynamic programming; Large eddy simulations (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117305700
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:113:y:2017:i:c:p:1033-1045

DOI: 10.1016/j.renene.2017.06.065

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 ().