Abstract
The grouping of turbines in large farms introduces that a wind turbine operating in the wake of another turbine and has a reduced power production because of a lower wind speed after rotor. The flow field in the wake behind the first row turbines is characterized by a significant deficit in wind velocity and increased levels of turbulence intensity. Consequently, the downstream turbines in a wind farm cannot extract as much power from the wind as the first row turbines. Therefore modeling wake effect is necessary because it has a great influence on the actual energy output of a wind farm. In this study, the adaptive neuro-fuzzy inference system (ANFIS) is designed and adapted to estimate wake effect in a wind farm according to wind turbine positions in wind farm, distances between turbines in the wind farm and rotor radius as well.
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