EconPapers    
Economics at your fingertips  
 

Design and optimization of airfoils and a 20 kW wind turbine using multi-objective genetic algorithm and HARP_Opt code

Krishnil R. Ram, Sunil P. Lal and M. Rafiuddin Ahmed

Renewable Energy, 2019, vol. 144, issue C, 56-67

Abstract: Small wind turbines (SWTs) are ideal for supplying electricity to small remote communities that do not have grid access. However, literature review and trends point out that SWTs are far from fully developed. While larger wind turbines have been researched extensively and perfected, SWTs lack improvements in efficiency and capacity factor. In the present work, airfoil sections for a 20 kW wind turbine were generated using Multi-Objective Genetic Algorithm. The USP07-45XX family of airfoils was designed to achieve maximum lift-to-drag ratio from 4 to 10° angles of attack and to be insensitive to leading edge roughness. The USP07-45XX airfoils showed only slight change during clean and soiled conditions both in experiments and in numerical studies. The optimized airfoils were used in the design of a 20 kW wind turbine. The turbine design and optimization code developed by National Renewable Energy Laboratory (NREL) – HARP_Opt – was used to design and optimize the 20 kW turbine. The turbine was designed using soiled airfoil characteristics of the USP07-45XX family of airfoils. Power curves show cut in speed of 2 m/s and a rated speed of 9 m/s. This gives an annual energy production (AEP) of 4.787 × 104 kWh while having leading edge soiling on blades. The high resistance of the airfoil to soiling means that the AEP will not vary from its design value due to the turbine blades getting dirty or soiled.

Keywords: Low Reynolds number airfoils; Genetic algorithm; Wind turbine; Blade design (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096014811830990X
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:144:y:2019:i:c:p:56-67

DOI: 10.1016/j.renene.2018.08.040

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 ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:144:y:2019:i:c:p:56-67