Offshore wind farm layout optimization regarding wake effects and electrical losses.

A major development of the offshore wind energy market is being witnessed. Since the implicated costs are considerably high, it is extremely important to ensure that the energy production is maximum, so that the costs per energy unit are minimized. Thus, the turbines should be strategically positioned to extract as much energy as possible from the wind, considering wake effect losses, as well as internal grid electrical losses. In order to avoid turbines to be placed in unrealistic positions, they should be distributed according to a grid of rectangular shaped cells; each of these is divided in multiple sub-cells. The problem of finding the turbines optimal position among the pre-defined sub-cells so that maximum annual energy is produced could be addressed using a deterministic approach. However, the problem becomes unfeasible when the number of turbines and/or the number of sub-cells increase. To overcome this difficulty, optimization techniques should be used. Genetic Algorithm and Particle Swarm Optimization are approached in this paper. This paper deals with the wind park layout optimization problem. A methodology to position the turbines inside a wind park so that the annual energy production is maximum is proposed. The results proved that the meta-heuristic method is much more CPU time efficient in providing the maximum annual year production as compared to the traditional deterministic approach. [ABSTRACT FROM AUTHOR]