Aerospace Science and Technology
Mahdi Azizi; Alireza Jahangirian
Abstract
To keep pace with current trends in the wind industry, this paper aims at the improvement of the annual energy production of a horizontal axis wind turbine by aerodynamic optimization of blades at the wind conditions of the Manjil site. To achieve this goal, the Riso wind turbine, whose characteristics ...
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To keep pace with current trends in the wind industry, this paper aims at the improvement of the annual energy production of a horizontal axis wind turbine by aerodynamic optimization of blades at the wind conditions of the Manjil site. To achieve this goal, the Riso wind turbine, whose characteristics are publicly available, is selected, and its twist angle and chord length distributions along the blades are optimized. The blade element momentum theory with appropriate corrections is used to predict the turbine output power. The genetic algorithm optimization tool, and Weibull probability density function, for wind regime representation, are also utilized in this work. Optimization results show a 9.4% and 11.6% increase in annual energy production, respectively, for the blade with optimal twist angle and the blade with optimal chord length and twist angle distributions. Finally, the superiority of selecting annual energy production as the objective function is assessed in comparison with other objective functions.
A. R. Jahangirian; M. Ebrahimi
Volume 11, Issue 1 , June 2017
Abstract
An efficient method for scattering Genetic Algorithm (GA) individuals in the design space is proposed to accelerate airfoil shape optimization. The method used here is based on the variation of the mutation rate for each gene of the chromosomes by taking feedback from the current population. An adaptive ...
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An efficient method for scattering Genetic Algorithm (GA) individuals in the design space is proposed to accelerate airfoil shape optimization. The method used here is based on the variation of the mutation rate for each gene of the chromosomes by taking feedback from the current population. An adaptive method for airfoil shape parameterization is also applied and its impact on the optimum design and convergence of the optimization process isinvestigated. In order to demonstrate the efficiency of the proposed method, a geometric inverse design using Genetic Algorithm is carried out and the capability of the method for producing airfoil shapes is assessed. The performance of the method is further evaluated by an aerodynamic shape optimization. Results indicate the merits of the method in increasing the maximum objective value about7percent as well as decreasing the total computational time up to28 percent.