Drag power kite with very high lift coefficient
Florian Bauer,
Ralph M. Kennel,
Christoph M. Hackl,
Filippo Campagnolo,
Michael Patt and
Roland Schmehl
Renewable Energy, 2018, vol. 118, issue C, 290-305
Abstract:
As an alternative to conventional wind turbines, this study considered kites with onboard wind turbines driven by a high airspeed due to crosswind flight (“drag power”). The hypothesis of this study was, that if the kite's lift coefficient is maximized, then the power, energy yield, allowed costs and profit margin are also maximized. This hypothesis was confirmed based on a kite power system model extended from Loyd's model. The performance of small-scale and utility-scale kites in monoplane and biplane configurations were examined for increasing lift coefficients. Moreover, several parameters of the utility-scale system were optimized with a genetic algorithm. With an optimal lift coefficient of 4.5, the biplane outperformed the monoplane. A 40 m wing span kite was expected to achieve a rated power of about 4.1 MW with a power density of about 52 kW/m2. A parameter sensitivity analysis of the optimized design was performed. Moreover, to demonstrate the feasibility of very high lift coefficients and the validity of a utilized simplified airfoil polar model, CFDs of a proposed high-lift multi-element airfoil were performed and the airfoil polars were recorded. Finally, a planform design of a biplane kite was proposed.
Keywords: Crosswind kite power; Drag power; Airborne wind turbine; High-lift airfoil; Biplane; Genetic algorithm (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117310285
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:118:y:2018:i:c:p:290-305
DOI: 10.1016/j.renene.2017.10.073
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 ().