Multi-criteria aerodynamic optimization of wind farm energy efficiency based on genetic algorithms

In this paper, the possibilities of using parallel processing algorithms and methodologies were analyzed in order to more efficiently solve the very complex problem of multi-criteria aerodynamic optimization in order to achieve the maximum energy efficiency of the entire wind farm, which is based on genetic optimization algorithms. It has been shown that the best results are obtained by applying the genetic algorithm method of distributive differential evolution. The program algorithm was written using MPI routines for communication between processors and was executed on a computer cluster located at the Faculty of Mechanical Engineering of the University of Belgrade within the SimLab laboratory.