RESUMEN
Wind energy technology, particularly power generation by wind turbines, has received substantial attention due to resource depletion and global warming concerns. These concerns highlight the importance of conducting studies to enhance their efficiency by increasing their power output. The goal of this work was to combine the RSM (Response Surface Methodology (RSM) with CFD (Computational Fluid Dynamics) to discover the optimal design parameters and conditions for ducted wind turbines. To that purpose, twenty-seven runs were chosen using Central Composite Design (CCD) in the design phase. Duct simulation was performed by employing different dimensional parameters and feeding them into a third-order polynomial that fitted to an eight-order function. The analyzed runs discussed the maximum available wind velocity and power at the throat area of the various designed ducts. The wind-enhanced power and speed were studied under different design parameters, and their effects were discussed. The optimum design conditions to capture maximum power were 0.16 m, 2, and 1.5 for design parameters of the duct's throat diameter, contraction ratio, and length-to-throat diameter ratio, respectively. A good selection of design parameters can increase the outpour power up to six times as a general result. By modeling CFD simulations using the RSM method, it is possible to minimize the time and cost of calculation to find the optimized range for the design parameters of the ducts.
RESUMEN
Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.