Wind-turbine design optimization using a many-objective evolutionary algorithm

In this work, we study the performance of an evolutionary algorithm for solving a real-world wind turbine design optimization problem which was a part of the Evolutionary Computation Competition 2019 organized by the Japanese Society of Evolutionary Computation. The problem involves 5 objectives, 32 continuous variables and 22 constraints, which are evaluated using WISDEM and OpenMDAO tools. The results obtained by the proposed algorithm are compared with several state-of-the-art algorithms to demonstrate its effectiveness.