Wind power has been widely considered and utilized in recent years as one of the most promising renewable energy sources. In the current research study, aerodynamic analysis of the upwind three-bladed horizontal axis turbine is carried out using blade element momentum theory (BEM), and a genetic algorithm (GA) is applied as an optimization method. Output power generation is considered as an objective function, which is one of the most common choices of objective function. The optimization variables also involve chord and twist distribution variations and the placement of the airfoil sections along the blade length. The optimal blade shape is investigated for the maximum output power at a specific wind speed, rotor diameter and airfoil profile. The modified BEM results are compared with an experimental measurement indicating reliable results. The results show that considering placement of the airfoils as design variables in addition to chord and twist rate has a significant effect on the optimal output power. Finally, the objective function (output power) is improved by 10% compared to the base function.
Tahani,M. , Sokhansefat,T. , Rahmani,K. and Ahmadi,P. (2014). Aerodynamic optimal design of wind turbine blades using genetic algorithm. Energy Equipment and Systems, 2(2), 185-193. doi: 10.22059/ees.2014.9895
MLA
Tahani,M. , , Sokhansefat,T. , , Rahmani,K. , and Ahmadi,P. . "Aerodynamic optimal design of wind turbine blades using genetic algorithm", Energy Equipment and Systems, 2, 2, 2014, 185-193. doi: 10.22059/ees.2014.9895
HARVARD
Tahani M., Sokhansefat T., Rahmani K., Ahmadi P. (2014). 'Aerodynamic optimal design of wind turbine blades using genetic algorithm', Energy Equipment and Systems, 2(2), pp. 185-193. doi: 10.22059/ees.2014.9895
CHICAGO
M. Tahani, T. Sokhansefat, K. Rahmani and P. Ahmadi, "Aerodynamic optimal design of wind turbine blades using genetic algorithm," Energy Equipment and Systems, 2 2 (2014): 185-193, doi: 10.22059/ees.2014.9895
VANCOUVER
Tahani M., Sokhansefat T., Rahmani K., Ahmadi P. Aerodynamic optimal design of wind turbine blades using genetic algorithm. Energy Equip. Syst., 2014; 2(2): 185-193. doi: 10.22059/ees.2014.9895