A Layout Investigation of Large Wind Farm in Akhfennir using Real Coded Genetic Algorithm

Abstract

The objective of this study is to evaluate the effect of wind turbine spacing in large wind farm on the total energy loss of the wind farm, the power loss is due to the wake effect between wind turbines, on a site gathering several wind turbines, if the wind turbines are too close, the loss of power increases with the wake effect. This paper presents an investigation into optimal wind farm layout in 88 wind farm configurations of a hypothetical WF in Tarfaya, to search the optimal number of Wind Turbines (WTs), the wind farm are Installed on an area of 35 km2 (7000m×5000m), with the aim to maximize the electrical power generated by all WTs and grows the annual economic profitability of the WF, in order to approve the result of this investigation a new approach based on the division of the wind farm in the sub domain method is proposed, to search the optimal location of Wind Turbines by mean an RCGA (Real Coded Genetic Algorithm). This new proposed approach is promising in terms of the applicability in large wind farm. It is also more suitable when performing the wind farm layout assessment in WPP (Wind Power Project).

Improved Design of a Large Offshore Wind Farm by Using Biogeography based Optimization

“…This optimization is known as the WF layout optimization problem (WFLOP). Some typical work using an approach based on genetic algorithms was performed by Mosetti et al [8], Grady et al [9], Emami et al [10], as well as Mittal [11] , Rajper [12] and Hassoine et al [13,14]. Using the same models of the WF and cost, Wan et al [15] and Pookpunt [16,17] demonstrated the optimal placement using Particle Swarm Optimization to maximize power production.…”