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Correction of various environmental influences on Doppler wind lidar based on multiple linear regression model

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  • Tang, Shengming
  • Li, Tiantian
  • Guo, Yun
  • Zhu, Rong
  • Qu, Hongya

Abstract

Doppler wind lidar (DWL) is being increasingly employed in various areas, such as wind energy, meteorology, aviation, and so on. Extensive studies have been conducted to validate its accuracy and reliability compared with anemometers mounted on meteorological towers. However, previous examinations mainly focused on a range up to 100 m because of the limited heights of meteorological towers. To further validate the DWL performance, especially above a height of 100 m, experimental tests were carried out at two national meteorological observatories in China (Shenzhen and Xilinhaote). The meteorological tower at Shenzhen Observatory is 356 m high, which enables validation of DWLs above 100 m. Different environmental variables, including humidity, precipitation, wind characteristics, and surface roughness length, were investigated to quantify their effects on the measurement errors of DWLs. Moreover, a correction methodology based on multiple linear regression model was proposed to eliminate the measurement error induced by environmental conditions. The corrected DWL data can be improved by up to 9.6% regarding the slope of the linear regression between the DWL and tower data, and the associated root mean square errors can be reduced by up to 37%.

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  • Tang, Shengming & Li, Tiantian & Guo, Yun & Zhu, Rong & Qu, Hongya, 2022. "Correction of various environmental influences on Doppler wind lidar based on multiple linear regression model," Renewable Energy, Elsevier, vol. 184(C), pages 933-947.
  • Handle: RePEc:eee:renene:v:184:y:2022:i:c:p:933-947
    DOI: 10.1016/j.renene.2021.12.018
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    References listed on IDEAS

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    1. Karthikeya, B.R. & Negi, Prabal S. & Srikanth, N., 2016. "Wind resource assessment for urban renewable energy application in Singapore," Renewable Energy, Elsevier, vol. 87(P1), pages 403-414.
    2. Torres Garcia, E. & Aubrun, S. & Coupiac, O. & Girard, N. & Boquet, M., 2019. "Statistical characteristics of interacting wind turbine wakes from a 7-month LiDAR measurement campaign," Renewable Energy, Elsevier, vol. 130(C), pages 1-11.
    3. Bottasso, C.L. & Pizzinelli, P. & Riboldi, C.E.D. & Tasca, L., 2014. "LiDAR-enabled model predictive control of wind turbines with real-time capabilities," Renewable Energy, Elsevier, vol. 71(C), pages 442-452.
    4. Chaurasiya, Prem Kumar & Ahmed, Siraj & Warudkar, Vilas, 2018. "Comparative analysis of Weibull parameters for wind data measured from met-mast and remote sensing techniques," Renewable Energy, Elsevier, vol. 115(C), pages 1153-1165.
    5. Dhiman, Harsh S. & Deb, Dipankar & Foley, Aoife M., 2020. "Lidar assisted wake redirection in wind farms: A data driven approach," Renewable Energy, Elsevier, vol. 152(C), pages 484-493.
    6. Jia, Chengzhen & Wang, Lingmei & Meng, Enlong & Chen, Liming & Liu, Yushan & Jia, Wenqiang & Bao, Yutao & Liu, Zhenguo, 2021. "Combining LIDAR and LADRC for intelligent pitch control of wind turbines," Renewable Energy, Elsevier, vol. 169(C), pages 1091-1105.
    7. Cortina, G. & Calaf, M., 2017. "Turbulence upstream of wind turbines: A large-eddy simulation approach to investigate the use of wind lidars," Renewable Energy, Elsevier, vol. 105(C), pages 354-365.
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    Cited by:

    1. Tang, Shengming & Guo, Yun & Wang, Xu & Zhu, Rong & Tang, Jie & Zhang, Shuai, 2023. "Evaluation and impact factors of Doppler wind lidar during Super Typhoon Lekima (2019)," Renewable Energy, Elsevier, vol. 205(C), pages 305-316.

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