Parameter optimisation of the Eolic Cell to augment wind power density through the Metamodel of Optimal Prognosis

Abstract

The present work advances a methodology to optimise variables involved in fluid dynamic phenomena for augmented wind turbines. Particularly, the study focuses on improving the performance of a convergent-divergent augmented wind turbine based on eolic cells designed to increase wind speed at the throat section, where a peripherally supported magnetic levitation rotor will be installed as part of a novel wind energy system for distributed generation. Previous studies focused on maximising average wind velocity as the target variable. In contrast, this study shifted its focus to power density, resulting in more effective and consistent results. Numerical axisymmetric computational fluid dynamics simulations were conducted to determine the impact of these improvements. Response surfaces were created for parametric analysis, and the metamodel of optimal prognosis was implemented to provide accuracy. The results indicate a significant improvement in available power, with an average increase of up to 12.5 times compared to non-augmented conditions.