Blade Dimension Optimization and Performance Analysis of the 2-D Ugrinsky Wind Turbine

Luke Sakamoto, Tomohiro Fukui and Koji Morinishi
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Luke Sakamoto: Department of Mechanical Engineering, Kyoto Institute of Technology, Kyoto 606-8585, Japan
Tomohiro Fukui: Department of Mechanical Engineering, Kyoto Institute of Technology, Kyoto 606-8585, Japan
Koji Morinishi: Department of Mechanical Engineering, Kyoto Institute of Technology, Kyoto 606-8585, Japan

Energies, 2022, vol. 15, issue 7, 1-14

Abstract: With the increasing focus on renewable energy, there is a need to improve the efficiency of vertical-axis wind turbines (VAWTs). The Ugrinsky wind turbine is a type of VAWT, but there are few studies on this turbine. Previous studies have shown that the maximum power coefficient of the Ugrinsky wind turbine reaches 0.170, which is 54.5% higher than that of the Savonius type (0.110), and this turbine maintains a high power coefficient over a wide range of tip speed ratios (TSR). In this study, the dimensions of the two semicircles of the Ugrinsky wind turbine were further optimized to obtain a higher power coefficient. An analysis of the effect of the blade dimensions on the performance was conducted. The flow around the turbine was simulated using the regularized lattice Boltzmann method. The geometry of the turbine was simulated using the virtual flux method for the Cartesian grid. The optimization was conducted in terms of the output power coefficient and the average value of the power coefficient for neighboring TSR to consider the fluctuation of the TSR. This study demonstrates that a closer vortex distance favored the growth of the vortex and improved the power coefficient.

Keywords: vertical-axis wind turbine (VAWT); Ugrinsky wind turbine; Savonius wind turbine; drag-type wind turbine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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