Abstract
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.
Publisher
Centre for Evaluation in Education and Science (CEON/CEES)
Reference14 articles.
1. B. Rašuo, A. Bengin, Optimization of Wind Farm Layout, FME Transactions, Vol. 38 No 3, pp 107-114, 2010;
2. B. Rašuo, A. Bengin, On Aerodynamic Optimization of Wind Farm Layout, PAMM, Vol. 10, Issue 1, pp. 539-540, doi: 10.1002/pamm.201010262, 2010;
3. B. Rašuo, M. Dinulović, A. Veg, A. Grbović, A. Bengin, Harmonization of new wind turbine rotor blades development process: A review, Renewable and Sustainable Energy Reviews, Volume 39, November pp. 874-882, doi: 10.1016/j.rser.2014.07.-137, 2014;
4. Mosetti G, Poloni C. and Diviacco B, Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 51, No. 1, pp. 105-116, 1994;
5. Moreno S. V, Wind Farm Optimisation, Centre for Renewable Energy Systems Technology, Loughborough University, Leicestershire, 2001;