조류터빈 최적설계 기법의 개선

Abstract

In this paper, we present the tidal current turbine optimal design tool improvements that we have developed since the initial presentation of this research. We first briefly review the existing code. Then, we show advanced optimization methods that can significantly improve the optimization efficiency using a hybrid optimization method that combines a genetic algorithm, a pattern search method, and a constrained simplex method. By comparing the newly developed hybrid method with 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).methods that can significantly improve the optimization efficiency using a hybrid optimization method that combines a genetic algorithm, a pattern search method, and a constrained simplex method. By comparing the newly developed hybrid method with 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).