Estimation of operational parameters of the counter-rotating wind turbine with artificial neural networks

The article presents the possibility of using artificial neural networks to model the operating parameters of a counter-rotation mini wind turbine. The work is based on data from wind turbine research results conducted in an aerodynamic tunnel in the Institute of Agricultural Engineering at the University of Environmental and Life Sciences in Wrocław. The correlation between the depended variable (generated power P) and independent variables (average velocity of the air stream v, wedge angle of the first rotor blades, wedge angle of the second rotor blades, distance between rotors) was examined. The quality of the network was verified based on the mean-square error. The construction of the turbine allows to steplessly change of the blades wedge angle and the distance between rotors. Hence in the future the constructed network model can be used for programming the controller allowing to optimize the operating parameters of the wind turbine to maximize the generated power.