Publications

Scanning and Simulating Flow with Floating Lidar Technologies (SSwiFT Wind)

October 2026

Characterization of the High Frequency Wave Spectrum Tail Measured by a Floating Lidar Buoy

June 2026

Buoys designed to measure wind using LiDAR are generally built to be stable, to enable accurate measurement of wind speed and turbulence. In addition to wind observations, wave information can be efficiently derived from the buoy’s motion sensors, offering a cost-effective and integrated solution without the need for dedicated wave instruments.

Performance Validation of Two Buoy-Mounted ADCPs Using a Subsea Reference in the Ionian Sea

June 2026

Acoustic Doppler Current Profilers (ADCPs) deployed on floating buoys present a compelling alternative to traditional seabed-mounted systems for current resource assessment. They simplify deployment in deep waters, facilitate real-time data transmission, and can be integrated into multi-sensor platforms, such as floating LiDAR buoys widely used in offshore wind assessment.

A Machine Learning-Based Predictive System for Marine Operability Forecasting

June 2026

This work presents a probabilistic machine learning framework for marine operability forecasting aimed at supporting offshore operational planning under uncertainty. The approach combines numerical weather prediction outputs from the ECMWF Integrated Forecasting System with high-resolution in situ measurements from EOLOS Floating LiDAR buoys.

Floating-Lidar-System-Generalized Machine Learning model for turbulence intensity correction

April 2026

In this study we present the evolution of the Eolos’ original machine learning (ML) turbulence intensity (TI) correction model. In 2024, Eolos developed a ML model specifically designed to correct TI measurements for the FLS200 buoy, a widely used floating lidar system.

A preliminary framework to compute reference-decoupled floating LiDAR uncertainty

April 2026

Reliable offshore wind resource assessment requires precise and transparent quantification of measurement uncertainty. Recent reconciliation studies show evidence that Floating LiDAR Systems (FLS) can achieve total uncertainties below 1% at hub height.

Enhancing floating ZX Lidar’s wind direction using high frequency yaw correction

June 2025

Taming Turbulence: A Comparison between Motion Compensation and Machine Learning for FLS measured TI

June 2025

Floating LiDAR Systems (FLS) are essential for delivering cost-effective and high-quality wind data in the offshore wind industry. While the 10-minute average Horizontal Wind Speed (HWS) measured by FLS compares well with traditional cup or sonic anemometers, significant discrepancies arise when assessing Turbulence Intensity (TI).

Measurement Uncertainty for the Envelope of Operational Conditions of the EOLOS Floating Lidar System

April 2025