Abstract
A new multi-objective method called Multi-Objective Electric Charged Particles Optimization (MOECPO) is proposed to optimally place wind turbines and at the same time select their optimal heights in an extensive area of wind farm considering several scenarios. This method permits the designer/planner to get several designs in just one run where the maximum efficiency and maximum output power are the objectives. Furthermore, while dealing with an optimization problem, reducing the number of design variables helps to simplify the problem and consequently improves the final solutions. In this paper, a smart approach which is based on binary coding is proposed and implemented for design variables reduction by a high factor. Under the scope of this research work, four case studies are investigated using two different sites and considering the same or different hub heights. The obtained Pareto set of solutions is represented by 96, 95, 199 and 209 solutions, for CASE 1, CASE 2, CASE3 and CASE 4, respectively. This front is spread over a large region and offers several interesting solutions with different number of turbines in the considered wind farm. The results or findings from the proposed approach allow the designer or planner to select the best solution or layout considering many factors. In addition, it can be used to plan the future extensions.