CFD analysis of gravity-fed drag-type in-pipe water turbine to determine the optimal deflector-to-turbine position

Abstract

AbstractIn-pipe hydroelectric power generation is a relatively new clean energy power generation technology. This new clean energy technology has been identified to be feasible after successful commercial installation in different parts of the world. Several researchers worldwide have studied the optimal turbine type, the optimal number of blades in turbine, introduction of suitable deflector, etc. for this technology. However, the effect of the turbine's position relative to the upstream deflector on its performance has not been studied so far. This research encompasses a numerical study of the in-pipe hydroelectric power generation turbine to identify the optimal position of the turbine from the deflector. The study was performed for a 160-mm diameter pipeline and a 126-mm turbine height and aims to predict the behavior of larger diameter pipelines for commercial installation. The numerical study was performed for a hollow-type drag turbine at 6 different rotational speeds and 10 different turbine positions. The results suggest that the performance characteristics of drag-type turbine are erratic, thus leaving little space to draw a firm conclusion about the turbine's performance. However, there was an increase in pressure difference, head and available theoretical power with the increase in rotational speed for all the positions. It was also found that such turbines were generally more efficient at slightly higher rotational speeds, i.e. speed greater than 40 rad/s, and at about the distance of 0.65D (where D is the pipe diameter) between deflector's eye and turbine.Highlights: • Drag-type water turbines can significantly contribute to the production of clean energy. • We varied the turbine position and rotational speed to see how these parameters affects the turbine performance. • Computational fluid dynamics approach is used to study the behavior of turbine at different operating conditions.