This work proposes a methodology to evaluate the performance of operating wind farms via the use of Supervisory Control and Data Acquisition System (SCADA) and modeled data. The potential annual energy is calculated per individual turbine considering underperforming/loss events to have their power output in accordance with a representative derived operational power curve. Losses/underperformance events are calculated and categorized into several groups aiming at identifying and quantify their causes. The methodology requires both anemometry data from SCADA system as well as modeled data. The discrepancy of the data representing the valid points of the power curve is taken into consideration as well when assessing the performance, i.e. wind speed vs power output of events that are not loss/underperformance. Production loss and relative standard deviation of power output of what is defined as “valid sample” in this work (per each turbine) are the main results obtained in this work. Finally, a number of optimization measures are suggested in order to enhance the performance, which can lead to a boost in the financial output of a wind farm. Aiming at judging the reliability of the proposed methodology, a case study is conducted and evaluated. The investigated case study shows that the methodology is capable of determining potential energy and associated losses/underperformance events. Several questions were raised during the assessment and are discussed in this report, recommendation for optimization measures are presented at the end of the study. Also, a discussion on the limitations and uncertainties associated to the presented methodology and the case study.