Optimization of Savonius wind turbine blades based on perturbed stochastic fractal search algorithm and Kriging surrogate model. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Zhang, Song; Xu, Shuhui
• Is Part Of: Energy sources. Volume 45:Issue 1(2023)
• Page Start: 2156
• Page End: 2173
• Publication Date: 2023-12-31
• Subjects: Savonius turbine -- Cubic Bezier curve -- Kriging -- Perturbed stochastic fractal search -- CFD; Natural resources -- Periodicals; Energy consumption -- Periodicals; Energy consumption -- Climatic factors -- Periodicals; Energy conversion -- Periodicals; Energy conversion -- Environment aspects -- Periodicals; Power (Mechanics) -- Periodicals; 333.7905
• DOI: 10.1080/15567036.2023.2186543
• Languages: English
• ISSNs: 1556-7036

Abstract

ABSTRACT: The shape of its blades would significantly affect the energy capture ability of the Savonius wind turbine. This work proposed an efficient and intelligent optimization design method for the shape of the blade. Firstly, the blade's shape is described parametrically using the cubic Bezier curve and then a certain number of design schemes in the design space are obtained using the Latin hypercube sampling technique, and the torque coefficients of these design schemes are evaluated using CFD simulation. Secondly, a Kriging model based on these design schemes and their corresponding torque coefficients is established. Thirdly, the optimal design scheme is obtained by taking the established Kriging model as an evaluation tool and taking the perturbed stochastic fractal search algorithm as an optimization tool and then verified using CFD. Through the above optimization method, a new type of blade is obtained. Compared with the traditional turbine with semi-circular blades, the turbine with the optimized blades can achieve about 9.03% improvement in energy capture efficiency at TSR = 1.