Posters

Abstract

Wind Lidars have become an established way to measure wind. Their measurement principles are well defined and understood. An extensive evidence base exists to demonstrate expected levels of performance and availability that largely support the broad needs of wind measurement campaigns. Certain, limited environmental conditions can cause a reduction in availability for any measurement sensor, for example the effects of icing on unheated cup anemometers. However, in situations where availability is reduced there is still an opportunity to enhance the availability by extrapolating from available measurement heights to a desired height, using well-established industry techniques. In this novel study, wind speeds are estimated using power-law shear extrapolation using two available, measured reference heights from a CW Lidar. IEC Classification data sets, Performance Verification data sets and real-world data sets are used to verify the validity of using extrapolation, while an assessment of the use of extrapolation instead of additional on-site measurements indicate that extrapolation performs at least as well as alternative on-site measurements at hub height. The investigation explores if an extrapolation methodology can be used in conjunction with a single measurement technology to provide a measurement solution that is appropriate in all environmental conditions with best-in-class data availability. Results are presented that demonstrate that CW Lidar can provide near 100% data availability at all heights whilst maintaining excellent regression statistics for IEC Classification and Performance Verifications. An innovate methodology for enhancing collected CW Lidar data is validated. The cost and uncertainty of wind measurement campaigns is reduced further when this methodology is deployed.