Projects per year
Abstract
Vertical axis wind turbines (VAWTs) are suitable for applications in urban areas. Their ultimate power production relies on both the structural parameters and wind conditions. In this study, the power performance of H-rotor VAWTs immersed in turbulence of various length scales was assessed via wind tunnel testing. The influence of turbine aspect ratio on the power performance was investigated in the turbulent flows. A range of length scales were produced by wooden grids of different mesh sizes. The power coefficients, CP, of the VAWTs were measured by connecting an external resistance in the rotor circuit. Uncertainty analysis of the experimental data was conducted thereafter. Encouragingly, the rated CP was raised by approximately 100% in the turbulent flows compared to that in the smooth flow. The results evidently proved that turbulence was favorable for the operation of VAWTs. Moreover, the rated CP was inversely proportional to length scale, whereas it increased with aspect ratio, irrespective of flow regimes, the underline reasons for which were addressed. Further, the power-law equations were proposed to mathematically express the length scale and aspect ratio effects. This study contributes to the design and application of VAWTs in built environments.
| Original language | English |
|---|---|
| Pages (from-to) | 121-132 |
| Journal | Energy |
| Volume | 173 |
| Online published | 30 Jan 2019 |
| DOIs | |
| Publication status | Published - 15 Apr 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Research Keywords
- Aspect ratio
- Length scale
- Power coefficient
- Turbulence
- VAWT
- Wind tunnel
RGC Funding Information
- RGC-funded
Fingerprint
Dive into the research topics of 'Power performance assessment of H-rotor vertical axis wind turbines with different aspect ratios in turbulent flows via experiments'. Together they form a unique fingerprint.Projects
- 1 Finished
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GRF: Ballasted Track Safety Monitoring under Operational Conditions by Bayesian Model Updating of the Coupled Train-track System
LAM, H. F. (Principal Investigator / Project Coordinator) & YANG, Y. B. (Co-Investigator)
1/10/16 → 8/09/20
Project: Research
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