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

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

Renewable Energy, 2022, vol. 184, issue C, 933-947

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%.

Keywords: Measurement error; Correction; Field experiment; Lidar; Multiple linear regression (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:184:y:2022:i:c:p:933-947

DOI: 10.1016/j.renene.2021.12.018

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