A study on measuring wind turbine wake based on UAV anemometry system. (October 2022)

• Record Type: Journal Article
• Authors: Li, Zhengnong; Pu, Ou; Pan, Yueyue; Huang, Bin; Zhao, Zhefei; Wu, Honghua
• Is Part Of: Sustainable energy technologies and assessments. Volume 53:Part B(2022)
• Publication Date: 2022-10
• Subjects: UAV anemometry system -- Field measurement of wind turbine wake -- Wind speed distribution -- Wake characteristics -- Wake model; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2022.102537
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: The wind measurement method for two UAV anemometry systems is proposed. The advantages of low cost and flexibility of the UAV anemometry system can improve the wind measurement efficiency. At 10D, the wake width was about 2.5 times the turbine diameter, the wake flow was considerably close to the incoming flow. The Gaussian-shape curve could better describes wind speed distribution on the horizontal plane of the wind turbine wake. The peak point for the normalized power spectrum of the wake wind was slightly different from that of incoming wind. Abstract: Unmanned aerial vehicle (UAV) wind measurement is a newly developed wind measurement method that can improve the efficiency of conventional wind measurements. A method for measuring the wake characteristics of wind turbines based on UAV is proposed. The research results show that when the downstream distance was 1D, the wake wind speed and turbulence intensity at the hub height are about 60–70% and 130–150% of the incoming flow, respectively. When the downstream distance was 10D, the wake wind speed and turbulence intensity at the hub height gradually recovered to about 90% and 110% of the incoming flow, respectively, and the wake width in the area was about 2.5 times the diameter of the turbine. The wind speed measured by UAV was in good agreement with that predicted by the AV model and the 3DJG model, indicating that the Gaussian-shape curve could better describe the wake wind speed distribution. The UAV anemometry system provides a new research approach for wind turbine wake wind field measurement and the assessment of in-service wind farm resources. Moreover, the results from this study provide a reference for the determination of wind turbine wake, generation power prediction, and structure design.