期刊
MACHINES
卷 10, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/machines10080687
关键词
multi-objective optimization; small wind turbine; renewable energy; turbine blade; airfoil; wind power; power coefficient; artificial neural network (ANN); startup behavior; wind potential
In this study, the performance of 10 low Reynolds number airfoils on small wind turbines was evaluated through a multi-objective optimization study. The type of airfoil was found to have a significant impact on not only the aerodynamic performance but also the startup performance of the turbine.
The type of airfoil with small wind turbine blades should be selected based on the wind potential of the area in which the turbine is used. In this study, 10 low Reynolds number airfoils, namely, BW-3, E387, FX 63-137, S822, S834, SD7062, SG6040, SG6043, SG6051, and USNPS4, were selected and their performance was evaluated in a 1 kW wind turbine in terms of the power coefficient and also the startup time, by performing a multi-objective optimization study. The blade element momentum technique was utilized to perform the calculations of the power coefficient and startup time and the differential evolution algorithm was employed to carry out the optimization. The results reveal that the type of airfoil used in the turbine blade, aside from the aerodynamic performance, completely affects the turbine startup performance. The SG6043 airfoil has the highest power coefficient and the BW-3 airfoil presents the shortest startup time. The high lift-to-drag ratio of the SG6043 airfoil and the low inertia of the turbine blades fitted with the BW-3 airfoil make them suitable for operation in windy regions and areas with low wind speeds, respectively.
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