Estimation of Aerodynamic Characteristics for a Horizontal Axis Wind Turbine

Abstract

Wind turbine aerodynamic characteristics play an important role in monitoring of condition and control of wind turbines in any wind
power plant. Accurate estimation of these wind turbine aerodynamic characteristics is required to more realistic prediction of size of the
storage capacity for wind energy integration. In this study, aerodynamic characteristics of horizontal axis wind turbine are modeled as a
function of wind velocity (UD) and atmospheric air temperature (Tatm) using artificial neural networks (ANNs). Wind velocity, UD and
atmospheric air temperature, Tatm are used as the input variables and wind power (P), power coefficient (CP), axial flow induction factor (a),
thrust coefficient (CT) and thrust (T) are computed as the output layer. The measured values are compared versus those predicted by the ANN
model and manufacture data. Results obtained from this study indicate that the ANN model can be a useful tool for accurate forecasting wind
turbine aerodynamic characteristics. The most advantage of this model is that as long as having the required hub-height wind speed, UD and
atmospheric air temperature, Tatm wind turbine aerodynamic characteristics can be predicted without detailed knowledge of turbine operations
and its control schemes.