Experimental computational analysis and deep learning techniques on wind velocity enhancement and prediction of novel invelox type wind turbine

Abstract

newline Wind energy is an alternative future energy to fossil fuels since it is abundant, more sustainable green energy. As a primary result, a unique high performance design is proposed with a diffuser-augmented wind turbine, including an intake funnel with guide vanes, natural fan, straight flow section, exit splitter with air openings, and end flange. This proposed design is an Integrated omni directional Intake funnel, Natural fan, Straight diffuser, Splitter, and Flange (I2NS2F) design. To construct thisI2NS2F configuration, four distinct wind turbines were developed: 1. Bare wind turbine, 2. Wind turbine diffuser design with single rotor turbine, 3. Bend diffuser, intake funnel, natural fan, splitter, and flange, and 4. I2NS2F design. newlineThe proposed designs are numerically studied using MATLAB Simulink and Ansys Fluent. Then, random search optimization optimizes these designs with Supervisory Control and Data Acquisition techniques to evaluate the wind velocity, and the performance is comparatively estimated. From this analysis, the I2NS2F design achieves 53m/s of wind velocity at the turbine region for 5.5m/s inlet wind, and it could be considered the highest wind velocity of the other three designs. Therefore, it is proved and concluded that the proposed I2NS2F design augments natural wind, resulting in greater green power generation.