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

• Published in: Renewable energy Vol. 144; pp. 56 - 67
• Main Authors: Ram, Krishnil R., Lal, Sunil P., Ahmed, M. Rafiuddin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2019
• Subjects: algorithms; Blade design; blades; electricity; energy; Genetic algorithm; Low Reynolds number airfoils; renewable energy sources; roughness; Wind turbine; wind turbines; Blade design; Low Reynolds number airfoils; Genetic algorithm; Wind turbine
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2018.08.040

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. •Blade sections for a 20 kW wind turbine are designed using a genetic algorithm code.•The objectives were to maximize lift-to-drag ratio for clean and soiled conditions.•The genetic algorithm code HARP_Opt was used for turbine design.•The power curves show a cut-in speed of 2 m/s and a rated speed of 9 m/s.•The airfoils are resistant to soiling ensuring consistent annual energy production.