The performance assessment of wind farms requires the acquisition of accurate power and wind speed data of each turbine. Nowadays, the nacelle anemometry is widely studied as an option for power performance verification. Therefore, systems to detect the nacelle anemometer faults in a wind farm in operation are necessary for maintenance purposes. In this paper, we propose a method to detect wind speed deviations of the nacelle anemometers by comparing them with the nearby anemometers. This comparison is made through an approach to estimate the wind speed in each nacelle. The approach is based on the discretization of wind speed data using the bin method. The key issue of this proposal is the estimation of the anemometer deviations considering the range of data with lower uncertainty. To this end, an average uncertainty model per bin and direction sector has been integrated into the method. The tests show that using wind speeds higher than 4.5 m s − 1 gives the lowest uncertainty. Data from two wind farms have been used to test this method, and the obtained results have allowed the detection of problematic anemometers. Copyright © 2012 John Wiley & Sons, Ltd.