AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM APPROACH FOR PREDICTION OF POWER FACTOR IN WIND TURBINES
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Abstract
This paper introduces an adaptive neuro-fuzzy inference system (ANFIS) model for predicting the power factor of a wind turbine. This model based on the parameters involved for NACA 4415 and LS1 profile types with 3 and 4 blades. In model development, profile type, blade number, Schmitz coefficient, end loss, profile type loss, and blade number loss were taken as input variables, while the power factor was taken as output variable. After a successful learning and training process the proposed model produced reasonable mean errors. The results on a testing data indicate that the ANFIS model is found to be more successful than the ANN approach in estimating the power factor.