Mohammed Amine Hassoine

The objective of this paper is to investigate the ability of analytical wake models to estimate the wake effects between wind turbines (WTs). The interaction of multiple wakes reduces the total power output produced by a large offshore wind farm (LOFWF). This power loss is due to the effect of turbine spacing (WTS), if the WTs are too close, the power loss is very significant. Therefore, the optimization of turbine positions within the offshore wind farm requires an understanding of the interaction of wakes inside the wind farm. To better understand the wake effect, the Horns Rev 1 offshore wind farm has been studied with four wake models, Jensen, Larsen, Ishihara, and Frandsen. A comparative study of the wake models has been performed in several situations and configurations, single and multiple wakes are taken into consideration. Results from the Horns Rev1 offshore wind farm case have been evaluated and compared to observational data, and also with the previous studies. The power output of a row of WTs is sensitive to the wind direction. For example, if a row of ten turbines is aligned with the 270° wind direction, the full wake condition of WTs is reached and the power deficit limit predicted by Jensen model exceeds 70%. When a wind direction changes only of 10° (260° and 280°), the deficit limit reduces to 30%. The obtained results show that a significant power deficit occurs when the turbines are arranged in an aligned manner. The findings also showed that all four models gave acceptable predictions of the total power output. The comparison between the calculated and reported power output of Horns Revs 1 showed that the differences ranged from - 8.27 MW (12.49%) to 15.27 MW (23.06%) for the Larsen and Frandsen models, respectively.

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).