A Design and Optimization of Multi-slot Diffusers for Power Augmentation in Small Axial Flow Wind Turbines

This study delves into a cutting-edge approach to boosting the efficiency of small urban wind turbines through the innovative use of power augmentation diffusers. Due to their compact size and the naturally low wind energy availability in urban areas, conventional small wind turbines often fall short in economic viability. Power augmentation, particularly using multi-slotted diffuser shrouds for boundary layer control (BLC), presents a promising solution. In this research various diffuser geometries are designed and tested using Ansys Fluent software and the SST k-ω turbulence model. The resulting data is integrated into an artificial neural network (ANN) and further optimized using both single-objective and multi-objective genetic algorithms (GA). Remarkably, the optimized designs demonstrate a significant increase in kinetic energy, with one geometry achieving nearly ۵ times the free-stream kinetic energy at the throat and another delivering over ۵.۳ times more at the throat and ۵۲% higher kinetic energy at the diffuser outlet. These breakthroughs offer valuable insights for the future of small wind turbine design, providing a pathway to more efficient, economically feasible solutions.

Keywords:

BLC diffuser , Optimization , Single-objective GA , Multi-objective GA , Flow separation , Airfoil