The power loss of a wind turbine due to wakes from upstream turbines is significant for a wind farm. This power loss is usually about 20% of wind turbine power, and this can increase to 40% for an extreme case. Such effects decrease the annual energy production of a wind farm. Thus, it is important to predict the effect of these types of wakes so as to maximize the power output of a wind farm. In this study, we investigate a method to control the pitch angle of turbines to maximize the aerodynamic power of a wind farm. The pitch angle of each wind turbine is controlled by its own pitch schedule or feedback algorithm to optimize the power output. However, these control methods cannot consider the effects of wakes, such as velocity defects and an increase of the turbulent intensity. Thus, controlling the pitch angle of the turbine does not guarantee the maximum aerodynamic power of the wind farm, which is why a comprehensive control method considering all of the wind turbines of a wind farm is needed. The blade element momentum theory (BEM) is used for the aerodynamic analysis. In addition, in order to evaluate the wind turbine wake, the eddy viscosity model (EVM) is used. The wake is assumed to be a two-dimensional Gaussian profile determined by the thrust coefficients of the fore-located turbines and the atmospheric conditions. A genetic algorithm (GA) was applied to calculate the optimal power. The results show that control of the pitch angle can maximize the power output of the wind farm. (C) 2012 Elsevier Ltd. All rights reserved.