Novel CFD and DMST Dual Method Parametric Study and Optimization of A Darrieus Vertical Axis Wind Turbine

Document Type : Regular Article

Authors

Turbomachinery Research Laboratory, Department of Energy Conversion, School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

The deteriorating effects of greenhouse gases resulting from the use of fossil fuels have led to increased public attention to renewable energy sources, with wind energy being a particularly favored option. This prompted the development of various wind turbine types' efficiency. This study intends to explore the influence of key design parameters consisting of the number of blades, blade chord length, helical angle, and J-shaped blade on the performance and self-starting ability of a Darrieus VAWT. Furthermore, implementing an efficient optimization model to obtain maximum power based on the numerical findings. To achieve this, two different numerical modeling approaches, namely Computational Fluid Dynamics (CFD) and Double Multi-Streamtube (DMST), have been applied. The results indicated that employing a higher blade number and chord length enhances the starting capability of the turbine. Moreover, increasing the helical angle to 60° reduces the generated torque fluctuations. Inspired by the design of the Savonius turbine, the implementation of a J-shaped airfoil boosted the Cp at low TSR. Finally, the Kriging optimization method has been employed to optimize the design parameters explored through CFD analysis. The outcomes showed that the optimum configuration of the examined Darrieus VAWT comprises a 3-bladed rotor with a blade chord length of 0.04 m and helical angle of 0° and a J-shaped blade length ratio of 0.68. This configuration yields an 10% increase in efficiency at the optimum TSR.

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References

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Journal of Applied Fluid Mechanics
Volume 17, Issue 1 - Serial Number 81
January 2024
Pages 205-218

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History

  • Received: 03 May 2023
  • Revised: 07 September 2023
  • Accepted: 12 September 2023
  • Available online: 01 November 2023

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