Presentations

Abstract

Floating lidar systems (FLS) have become central to the assessment of offshore wind resources, particularly where alternative measurement technologies such as fixed meteorological masts or scanning lidar systems are impractical. Progressive development in international best-practice has facilitated the acceptance of FLS data within bankable wind resource and energy yield assessments. Early roadmaps for commercial acceptance, driven largely by industry-led initiatives such as the Carbon Trust Offshore Wind Accelerator, adopted conservative approaches to the treatment of measurement uncertainty. Subsequent reviews of lidar uncertainty methodologies highlighted the need for a consistent, standardised framework for data capture, reporting and uncertainty evaluation. This culminated in the publication of IEC 61400-50-4, which provides a structured uncertainty framework and includes provisions for the use of multiple lidars installed on a single FLS. However, the standard implicitly assumes either a single lidar or multiple lidars of the same type and offers limited guidance on mixed-manufacturer configurations or the potential reduction in measurement uncertainty arising from their combined use. This study evaluates measurement uncertainty from a six-month offshore campaign in which two vertically profiling lidars from different manufacturers - a continuous-wave ZX300 and a pulsed-wave Vaisala WindCube - were co-located on a single Green Rebel FLS. The FLS was deployed at the National Offshore Anemometry Hub (NOAH), where simultaneous measurements were obtained against Class 1 cup anemometers at 52 m, 69 m, 86 m, and 103 m above mean sea level. Higher-altitude reference data were obtained from a fixed ZX300 installed on the NOAH platform and from an independent dual-scanning lidar configuration. Overall measurement uncertainty was evaluated following the IEC framework. The analysis considered three configurations: each lidar operating independently, and a combined dual-lidar configuration in which measurements from both systems were jointly considered. Uncertainty components associated with the floating platform, mounting configuration, and environmental influences were treated consistently across all configurations. Each lidar was first evaluated as if operating in isolation, with the presence of a second lidar assumed not to introduce additional uncertainty related to calibration, installation, or system interaction. This ensures that differences in resulting uncertainty estimates arise solely from the treatment of multiple independent measurements rather than from changes in assumed system performance or classification. For the combined dual-lidar configuration, uncertainty was propagated using the same IEC framework, with consideration of correlation between the two lidars. The analysis examines how differing lidar technologies and manufacturer-specific characteristics influence the resulting combined uncertainty relative to configurations employing either a single lidar or multiple lidars of the same type. In addition to the formal uncertainty assessment, the implications of dual-lidar deployment for campaign robustness, measurement quality and data completeness are considered. While not directly reflected in the uncertainty calculation, the presence of a second lidar provides operational redundancy and the potential to mitigate data loss during system outages or degraded performance. The findings provide practical insight into the treatment of mixed-manufacturer dual-lidar configurations within the existing IEC framework and may help inform future guidance on the use of measurement redundancy to balance uncertainty reduction, data quality, and campaign resilience.