Computational and experimental optimization of the exhaust air energy recovery wind turbine generator

This paper studies the optimization of an innovative exhaust air recovery wind turbine generator through computational fluid dynamic (CFD) simulations. The optimization strategy aims to optimize the overall system energy generation and simultaneously guarantee that it does not violate the cooling tower performance in terms of decreasing airflow intake and increasing fan motor power consumption. The wind turbine rotor position, modifying diffuser plates, and introducing separator plates to the design are considered as the variable factors for the optimization. The generated power coefficient is selected as optimization objective. Unlike most of previous optimizations in field of wind turbines, in this study, response surface methodology (RSM) as a method of analytical procedures optimization has been utilised by using multivariate statistic techniques. A comprehensive study on CFD parameters including the mesh resolution, the turbulence model and transient time step values is presented. The system is simulated using SST K-ω turbulence model and then both computational and optimization results are validated by experimental data obtained in laboratory. Results show that the optimization strategy can improve the wind turbine generated power by 48.6% compared to baseline design. Meanwhile, it is able to enhance the fan intake airflow rate and decrease fan motor power consumption. The obtained optimization equations are also validated by both CFD and experimental results and a negligible deviation in range of 6-8.5% is observed.