Genetic algorithm for optimizing blade of wind turbine by direct-forcing immersed boundary modeling

• Main Authors: Chao-Ching Kao, 高晁慶
• Other Authors: Ming-Jyh Chern
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/3j66b3

碩士 === 國立臺灣科技大學 === 機械工程系 === 107 === Renewable energy is an important topic due to energy shortage. Especially wind energy converted by a wind turbine receives more attentions. In the present study, the blade design of the wind turbine using a couple method with computational fluid dynamics (CFD) and genetic algorithm (GA) is discussed. The blade shape is the most significant effective factor in the wind energy conversion. Hence, we dedicated to utilizing an optimal method for the cross-section of blade, i.e., an airfoil, in order to get the better efficiency for producing the higher lift and lower drag to drive the wind turbine. According to the previous study, the Genetic Algorithm (GA) is known to be the robust method in the optimal design area. The real-coded Genetic algorithm is considered since it is able to solve the defect of binary code. That is, the chromosomes length is too long to code. While the PARSEC parameterization method is used to represent the shape of airfoil through the eleven parameters as the control variables. Furthermore, a direct-forcing immersed boundary (DFIB) method is employed for simulations of interaction of rotating blades in a flow field at a moderate low Reynolds number. Numerical results reveal that the shape of airfoil can be optimized and the proposed DFIB model coupled with GA successfully simulates the moving blade in flow field for obtaining the high performance.