Design optimization through performance investigation of diffuser augmented wind turbine using CFD

Abstract

Currently, developed and developing countries are investing many resources in the development of renewable energy to harness the global ef ects of the planet’s energy. Among these renewable energy types, the most environmentally friendly one is wind energy. Many large-scale wind farms have been excavated by many studies using high wind flows. However, maximizing wind energy at low speeds is a significant challenge for small-scale wind turbines. literatures has suggested and used wind turbines inside dif users to optimize wind speeds, and studied parametric studies. Still, there are challenges that no optimum shape and size of dif user. In this sense, systems that have been created have not proven to be at their optimum stage. In this study, the optimum 3D geometry and shapes of dif erent dif users in terms of the optimum velocity the dif user produces were identified, and the comparison of wind turbines with and without dif users was compared and identified by using computational fluid dynamics in ANSYS fluent with an average inlet wind speed of 4.5m/s. According to the size analysis of the dif user inlet- shroud (0–22) angle and flange height (0.1–0.8) ratio with the ultimate opening angle, an increase of 82.9% in velocity was obtained at 24 inlet-shroud and 0.3 flange height. In the shape study of the dif user, the inlet shroud side lower curved flange had an optimum velocity of 9.12 m/s (maximum) and 8.2 m/s (average), resulting in 102.66% and 82.2%, respectively. Large increments of velocity around the dif user inlet at 0.175 m were observed, and a wind turbine was placed at this maximum location. The wind turbine with an optimized dif user demonstrated an increased velocity of 11 m/s with a velocity increment factor of 2.44 compared to a bare wind turbine and a power coef icient of 44% compared to a bare wind turbine of 38.072%. Optimized dif user-augmented wind turbines result in a reduction of the levelized cost of energy by 85.83%. The results of this work were validated with experimental work from the literature, which shows good agreement. Finally, experimental work, field tests, and additional detailed optimization work were suggested.