Optimization of Blade Geometry of Savonius Hydrokinetic Turbine Based on Genetic Algorithm

Abstract

Savonius hydrokinetic turbine is a kind of turbine set which is suitable for low-velocity conditions. Unlike conventional turbines, Savonius turbines employ S-shaped blades and have simple internal structures. Therefore, there is a large space for optimizing the blade geometry. In this study, computational fluid dynamics (CFD) numerical simulation and genetic algorithm (GA) were used for the optimal design. The optimization strategies and methods were determined by comparing the results calculated by CFD with the experimental results. The weighted objective function was constructed with the maximum power coefficient C p and the high-power coefficient range R under multiple working conditions. GA helps to find the optimal individual of the objective function. Compared the optimal scheme with the initial scheme, the overlap ratio β increased from 0.2 to 0.202, and the clearance ratio ε increased from 0 to 0.179, the blade circumferential angle γ increased from 0°to 27°, the blade shape extended more towards the spindle. The overall power of Savonius turbines was maintained at a high level over 22%, R also increased from 0.73 to 1.02. In comparison with the initial scheme, the energy loss of the optimal scheme at high blade tip speed is greatly reduced, and this reduction is closely related to the optimization of blade geometry. As R becomes larger, Savonius turbines can adapt to the overall working conditions and meet the needs of its work in low flow rate conditions. The results of this paper can be used as a reference for the hydrodynamic optimization of Savonius turbine runners.