Screening analysis and unconstrained optimization of a small-scale vertical axis wind turbine

• Autor(a) principal: Trentin, Pedro Francisco Silva [UNESP]
• Data de Publicação: 2022
• Outros Autores: Martinez, Pedro Henrique Barsanaor de Barros [UNESP], dos Santos, Gabriel Bertacco [UNESP], Gasparin, Elóy Esteves [UNESP], Salviano, Leandro Oliveira [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.energy.2021.122782; http://hdl.handle.net/11449/223008
• topic: Computational fluid dynamics; Optimization; Response surface methodology; Vertical axis wind turbine

The demand for alternative and renewable energy sources has been substantially growing in recent years, mainly steered by economic and environmental inconveniences of conventional energy sources, such as oil and its derivatives. In this context, wind energy has emerged as an attractive renewable source, envisioning possibilities of developing more efficient equipment to meet the ever-growing energy demand. In this work, we coupled Computational Fluid Dynamics (CFD) with an optimization based on response surface (RS) methodologies to find an optimal design for a small-scale NACA 0021 Darrieus vertical axis wind turbine (VAWT) operating at a tip speed ratio of 2.63. For that, we investigated four geometric parameters: number of blades (N), rotor diameter (D), chord length (c), and pitch angle (β). For the numerical model, we considered a two-dimensional, incompressible, turbulent, and unsteady flow regime. A sensitivity analysis (SA) via Morris’ method was performed to identify the influence of the four geometric parameters on the turbine aerodynamic performance. Our results reveal that the pitch angle (β) contributes the most (58%) to the turbine performance. The resulting optimized turbine design increased the conversion efficiency by 40%. Additionally, we also present a detailed discussion on the flow phenomenology considering the impact of each one of the four geometric parameters on the power coefficient. Finally, the strategy adopted here, in which a qualitative sensitivity analysis combined to the response surface and unconstrained optimization, was shown to be robust and can be applied to high-dimensional and computational-expensive CFD models to reduce costs with adequate results regarding fluid flow phenomena.