Posters

Abstract

Ground-based lidar is a promising wind measurement technology in wind resource assessment and power performance testing. This study provides a method for correcting wind measurements obtained from ground-based lidar by estimating measurement errors through Variational Data Assimilation (VDA). Ground-based lidar emits signals and measure backscatter to determine atmospheric wind velocities. Existing methods often fail in complex terrains due to inaccuracies in wind reconstruction. The proposed method integrates available measurements into wind flow simulations, enhancing accuracy. It uses VDA to optimize wind flow models, reducing computational requirements while maintaining accuracy. Additionally, it considers the Range-Weighting-Function (RWF) of lidars for realistic evaluation of radial velocities along the Line-Of-Sight (LOS). Validation was conducted at four sites in China and results shows that the new method delivers comparable correction performance to conventional CFD correction methods, particularly in low to moderate complexity terrain. this new method can run in about two minutes on limited hardware, and provide the possibility to be embedded into the ground-based lidar to achieve the real-time correction.The study provides a high-accuracy, lightweight correction method applicable in real-time scenarios, ensuring precise wind measurements essential for various applications including wind energy projects and meteorology.