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.
PO120: METICE Validation: Cup Equivalent Transfer Function for Continuous Wave Lidar
Euan Macdonald, Senior Data Scientist, ZX Lidars
Abstract
Turbulence Intensity (TI) is a fundamental metric in wind energy, influencing turbine design, site suitability assessments, and certification procedures. Conventionally, TI is measured using cup anemometers (TICUP), which provide point-based observations but are constrained by mechanical response times and limited spatial representation. In contrast, continuous wave (CW) lidars offer enhanced deployment flexibility and remote sensing capabilities, though they differ from cup anemometers in both spatial sampling - measuring over a conical volume - and temporal resolution, which is governed by scanning rates. These inherent differences introduce systematic biases between lidar-derived TI (TICW) and TICUP, particularly as a function of height and atmospheric stability. To bridge this gap, machine-learning correction models derive cup-equivalent TI (TICE) from CW lidar data. ZX Lidars’ Multisite Ensemble TICE (METICE) uses an ensemble in which each base model is trained on a single location; predictions are then aggregated with adaptive weights proportional to each model’s expected local performance. For example, under high-shear conditions, models that perform better in high shear receive greater weight. In so doing, the approach maximises the chance that the most relevant information drives the estimate and improves generalisation across sites and conditions. METICE uses basic inputs: 10-minute mean wind speed, standard deviation, height and shear coefficient.
No recording available for this poster.
