Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm

A multi-objective optimization process for wind turbine steel towers is described in present work. The objective functions are tower top deformation and mass. The tower’s height,radius and thickness are considered as design variables. The mathematical relationships between objective functions and variables were predicted by adopting a response surface methodology(RSM).Furthermore,the multi-objective non-dominated sorting genetic algorithm-II(NSGA-II) is adopted to optimize the tower structure to achieve accurate results with the minimum top deformation and total mass. A case study on a 2 MW wind turbine tower optimization is given,which computes the desired tower structure parameters. The results are compared with the original tower: a reduction of tower top deformation reduction by about 16.5% and a reduction of a mass by about 1.5% could be achieved for such an optimization process.