Posters
Come meet the poster presenters to ask them questions and discuss their work
We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in industry and the academic community.
On 9 April at 17:15, we’ll also hold the main poster session and distinguish the 7 best posters of this year’s edition with our traditional Poster Awards Ceremony. Join us at the poster area to cheer and meet the laureates, and enjoy some drinks with all poster presenters!
We look forward to seeing you there!
PO138: Numerical evaluation of the smearing effect in aspinner-mounted lidar for wind field reconstruction
Esperanza Sagredo, PhD student, DTU
Abstract
This study investigates the impact of the smearing effect on wind field reconstruction using a spinner-mounted lidar on a wind turbine. Nacelle-mounted lidars, though essential for wind measurements, suffer from blade blockage, reducing data accuracy. Spinner-mounted lidars, however, eliminate this issue by providing high measurement availability across the rotor plane. A key challenge with this technology is the smearing effect, which arises due to the beam's rotation with the rotor. This smearing occurs as the beam samples along an arc rather than a single point, and the extent of the effect depends on the lidar's sampling frequency. To assess this effect, we use numerical data extracted from a reference wind field, generated from LES data, using the numerical lidar sensor available in HAWC2 v13.1. Wind fields are reconstructed using Inverse Distance Weighting (IDW) interpolation, with and without accounting for smearing, across varying beam sampling times (from 0.1 to 0.5 seconds). Comparisons are made against a reference wind field, ensuring accuracy in the reconstruction. The results show that smearing improves reconstruction accuracy, reducing the Mean Absolute Error (MAE) by up to 2.79% for a sampling time of 0.5 seconds. Additionally, the study highlights that the lidar's sampling time plays a more significant role in determining reconstruction accuracy than smearing alone, with errors increasing by 12.84% when comparing a 0.1-second sampling time to 0.5 seconds. Despite fewer available measurements at higher sampling times, smearing mitigates errors by averaging multiple data points, reducing discrepancies in critical regions. In conclusion, while both smearing and sampling time affect reconstruction accuracy, smearing proves beneficial in smoothing errors, particularly in areas where fewer measurements are available.
No recording available for this poster.
