Recent improvement of optimization methods in a tidal current turbine optimal design tool

In this paper, we present the current turbine optimization design tool improvements implemented since the initial presentation of this tool in 2009. We first briefly review the existing code. Then, we show advanced optimization methods that can significantly improve the efficiency using a hybrid method that combines a genetic algorithm, a pattern search method, and a constrained simplex method. By comparing the newly developed hybrid method with the previously implemented genetic algorithm, we found that the hybrid optimization scheme can reduce the computation time by over 30%, while still obtaining similar or higher quality solutions. Additionally, we discuss the extensive improvements, focusing on the final objective function value, computation time, optimal design (including blade shape, rpm, and pitch angle), and power curve, with respect to current velocity and loads (including torque, thrust force, and root-flap bending moment).