Shape optimization of a shrouded Archimedean-spiral type wind turbine for small-scale applications

Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology

“…Shrouded wind turbines enhance wind energy capture by increasing wind velocity as it passes through the throat region of ducts while retaining the original energy extraction method employed by bare wind turbines [7,8]. Numerous studies suggest that shrouded wind turbines can outperform their bare counterparts, producing more wind power at lower cut-in wind speeds and allowing for extended operation throughout the year [7,[9][10][11].…”

“…Additionally, shrouded turbines may surpass the Betz limit, signifying peak efficiency and mitigating energy losses related to tip vortices [10][11][12][13]. Shrouded wind turbines offer additional advantages, including noise reduction, reduced risk of blade failure, improved bird safety, and enhanced performance in turbulent environments [14].…”

“…Concurrently, the augmentation of velocity for diffusers is significantly influenced by the length of the diffuser and its opening angle [31][32][33][34]. Moreover, adding a flange to the diffuser is thought to further improve velocity augmentation [11,[35][36][37]. While the cylindrical section primarily serves as a housing for the turbine, its throat length is crucial as it can influence airflow, thereby affecting velocity augmentation.…”

“…The work in [32] highlighted the critical role of throat section length in shrouded wind turbine systems, emphasising its significance in preventing nonuniform velocity distribution before the turbine and potential flow separation behind the rotor, particularly at the diffuser's outlet. Adding a flange to the diffuser exit creates a low-pressure region, drawing more mass flow and causing wind turbines to rotate and automatically align with changes in wind direction [11,26].…”

“…The extreme learning machine surrogate outperformed with the smallest root mean square error at 11.24%, followed by kriging at 17.64% and response surface at 22.17%. The authors of [11] optimised the Archimedean-spiral type wind turbine (ASWT) for off-grid power generation using an evolutionary algorithm with a kriging model and computational fluid dynamics simulations. The optimised shroud design achieved a remarkable Cp of 0.502, a 2.58-fold increase over the bare ASWT's Cp of 0.195 at a tip speed ratio of 2.5.…”