Abstract
Wind turbine blades made of CF/GF hybrid blades are expected for the next generation large wind turbine. The hybrid blade is made from Carbon Fiber Reinforced Plastic and Glass Fiber Reinforced Plastic, and structural optimization of the blades is a multi-objective optimization problem (MOOP) on weight reduction and cost reduction. In the present paper, the MOOP is solved using Multi-Objective Genetic Algorithm (MOGA). The turbine blade structure has to satisfy constraints with respect to ultimate strength, fatigue strength, buckling and deflection. To evaluate these constraints, full scale FEM analyses are indispensable, and. this requires enormous computational cost. In this paper, to reduce the cost, Kriging model response surface approximations for the surrogate model of the constraint satisfaction are constructed. Since Pareto solutions obtained using Kriging model response surface do not always satisfy the constraints, the obtained results are confirmed to check the satisfaction of the constraints using FEM analyses. Using the FEM results, Kriging response surfaces are improved to fit more accurately around the Pareto optimal results. Some new approaches to judge for improvement of Kriging response surface on designing wind turbine blade are tried. As a result, CF/GF wind turbine blade is successfully optimized with low calculation cost.
