Abstract

Vertical axis wind turbines (VAWTs) have received growing interest for off-shore application and in the urban environments mainly due to their omni-directional capability, scalability, robustness, low noise and costs. However, their aerodynamic performance is still not comparable with their horizontal axis counterparts. To enhance their performance, the impact of operational parameters such as tip speed ratio (λ), Reynolds number (Rec) and turbulence intensity (TI) on their power performance and aerodynamics needs to be deeply understood. The current study, therefore, intends to systematically investigate the effect of these parameters in order to provide a deeper insight into their impact on the aerodynamic performance of VAWTs. For this investigation, a Darrieus H-type VAWT has been employed. A wide range of the parameters is considered: λ = 1.2–6.0, Rec = 0.3 × 105–4.2 × 105 and TI = 0%–30% to analyze the turbine performance, turbine wake and dynamic loads on blades. High-fidelity computational fluid dynamics (CFD), extensively validated with experimental data, are employed. The results show that (i) variable-speed operation maintaining the optimal λ at different wind speeds improves the turbine power coefficient, e.g. up to 168% at 4 m/s, while keeping an almost constant thrust coefficient, (ii) the turbine performance and wake are Re-dependent up to the highest Rec studied, (iii) large TI (> 5%) improves the turbine performance in dynamic stall by promoting the laminar-to-turbulent transition and delaying stall on blades, however it deteriorates the optimal performance by introducing extra skin friction drag. The findings of the current study can support more accurate performance prediction of VAWTs for various operating conditions and can help the improvement of the aerodynamic performance of VAWTs.

Highlights

  • Vertical axis wind turbines (VAWTs) have received growing interest [1,2,3,4,5,6,7] for off-shore applications [8,9,10] as well as the built environment where they have the potential to be installed on the roof [11], included in the façade [12,13,14,15] or between buildings [16]

  • The results show that (i) variable-speed operation maintaining the optimal λ at different wind speeds improves the turbine power coefficient, e.g. up to 168% at 4 m/s, while keeping an almost constant thrust coefficient, (ii) the turbine performance and wake are Reynolds number (Re)-dependent up to the highest Rec studied, (iii) large turbulence intensity (TI) (> 5%) improves the turbine performance in dynamic stall by promoting the laminar-to-turbulent transition and delaying stall on blades, it deteriorates the optimal performance by introducing extra skin friction drag

  • It should be noted that the pressure distribution on the blade suction side can be employed to identify the boundry layer events: (i) the sudden change in the rate of pressure recovery typically signals the beginning of a laminar separation bubble (LSB), (ii) the follow-up abrupt increase in pressure prompts laminar-to-turbulent transition onset and (iii) the second sudden change in rate of pressure recovery shows the end of LSB, from which the length of LSB can be estimated [108,109]

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Summary

Introduction

Vertical axis wind turbines (VAWTs) have received growing interest [1,2,3,4,5,6,7] for off-shore applications [8,9,10] as well as the built environment where they have the potential to be installed on the roof [11], included in the façade [12,13,14,15] or between buildings [16]. The vast majority of these studies focused on the impact of λ on power coefficient CP, while less attention has been paid to the detailed analysis of aerodynamics and dynamic loads on turbine blades These studies did not investigate the optimal turbine operation by maintaining the optimal λ versus wind speed. Such investigations could highlight the benefits of maintaining the optimal tip speed ratio for VAWTs. The prime effect of Reynolds number (Re) on boundary layer events and the aerodynamic performance of static airfoils is well shown in the literature [69,70,71,72,73,74,75].

Computational settings and parameters
Solution verification and validation
Impact of tip speed ratio
Loads on blades
Turbine performance
Turbine wake
Optimal tip speed ratio
Impact of Reynolds number
Impact of turbulence intensity
Findings
Summary and conclusions
Full Text
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