Performance analysis of multi-stage gravitational water vortex turbine

Highlights: • Offset increase between two runners in a conical basin re-originates the vortex. • Undistorted surface vortex has more energy available for power generation. • Head utilization capacity of top runners dictate the performance of bottom runners. • Rotors ratio of runners must be similar to rotor diameter to basin diameter ratio. • Multi-staging in GWVT increase the overall performance. -- Abstract: In this study, the performance of a multi-stage gravitational water vortex turbine (GWVT), which is assembled in a conical basin, is investigated analytically and experimentally. Each runner of the multi-stage GWVT is independent in terms of power generation through telescopic shaft arrangement. Performance parameters, such as rotational speed, torque, power and efficiency, are analyzed under various load conditions in which the effects of design parameters, such as rotors ratio, offset distance between neighbouring runners, and intra-staging and inter-staging of two-stage and three-stage GWVT, are considered. In the multi-stage GWVT, the profile of the blades of upstream runners result in minimal vortex distortion. Thus, the power generation capacity of downstream runners are ultimately enhanced because the performance of latter runners strongly depend on the head utilization capacity of the former runner. Furthermore, the runners with blades tilted on a vertical plane are best suited for the position near the bottom of the basin, whereas cross-flow blades are recommended at the top position. Moreover, the present study suggests that the rotors ratio of the neighbouring runners be selected in such a way that the two runners have the same rotor-to-basin diameter ratio with optimum offset distance. Multi-staging in GWVT demonstrates the development of a combined effect of solid body rotation and free vortex. It also shows a prominent improvement in the overall performance of the turbine compared with that of single-stage GWVT. The proposed mathematical model successfully predicts the experimental results qualitatively and quantitatively, thereby proving its reliability and robustness.