Wind Energy scientific digest 2025

Onshore, lidar turbulence intensity (TI) biases compared to cup anemometers have remained a barrier to full lidar acceptance. This work shows how improving lidar TI reconstruction can enable further replacement of met masts for wind energy applications. A methodology based on inter‑beam reconstruction delivers major improvements in regression statistics and mostly meets DNV‑RP 0661 KPIs.

This presentation explores why lidar‑assisted control (LAC) is not yet widely adopted on wind turbines, despite clear benefits in load reduction, energy capture, and turbine life extension. Drawing on large‑scale field experience from hundreds of deployed nacelle lidars, this work shows how robust, industrialized LAC can close the gap between simplified theoretical predictions and real‑world turbine performance and scale from pilot projects to standard turbine technology.

Ørsted presents a breakthrough methodology for more accurate lidar calibration using fiber optics and Monte Carlo uncertainty propagation. The study compares traditional met‑mast‑based calibration with lab‑ and simulation‑based approaches, quantifying the impact on overall measurement uncertainty for long‑term wind assessments.

This poster evaluates whether dual‑scanning lidars (DSLs) or floating lidars (FLSs) are better suited for offshore wind resource assessment in Turkey. Using a validated theoretical error model and geospatial analysis of three planned offshore wind zones, it maps the expected measurement uncertainty of DSLs and compares it with a representative FLS uncertainty. The results show that, where good beam geometry is possible and sites lie within scanning range, DSLs can achieve lower or comparable uncertainty to FLSs while also providing valuable spatial information for wind farm design.

This poster validates two new post‑processing algorithms for WindCube 2.1 XP:                                     a three‑line‑of‑sight (3LOS) reconstruction and a deep‑learning range‑boosting (RB) filter. Using measurements up to 200 m, compared against an IEC‑compliant met mast, the algorithms recover additional valid data (about 5% more availability, depending on site and height) by intelligently using three beam configurations and classifying low‑signal measurements, without artificially generating data. The recovered wind speeds and directions remain highly consistent with the reference mast, preserving measurement accuracy and data integrity.