Come meet the poster presenters to ask them questions and discuss their work
Check the programme for our poster viewing moments. For more details on each poster, click on the poster titles to read the abstract. On Wednesday, 6 April at 15:30-16:15, join us on Level 3 of the Conference area for the Poster Awards!
PO245: Nacelle lidars for wake detection and waked inflow energy loss estimation
Matt Smith, ZX Lidars
Downstream turbines in a turbine array can often experience waked inflows from upstream turbines. This can result in increased loading of those turbines, as well as an overall decrease in the windfarm efficiency. Wake steering is an approach where upstream turbines are typically yawed to try and ensure downstream turbines experience cleaner and unwaked inflows. Computational fluid dynamics (CFD) and windtunnel experiments can be used to help inform such farm optimisations. Additionally, some circular scan continuous-wave nacelle-mounted lidars can be used to both detect the presence of wakes in real-time and quantify the impact on energy yield of the instrumented turbines. They can form an important part of practical farm optimisation, especially where turbine layouts or terrain effect make CFD predictions unreliable or difficult to simulate in windtunnels. This paper presents the results of wake measurement investigations from a sophisticated measurement campaign performed concurrently on 14 turbines. The turbines were selected from 30 turbines in a recently commissioned windfarm. Each of the selected turbines was instrumented with a nacelle-mounted circular scan multirange CW lidar. The windfarm was situated in Western Scotland. Terrain and the presence of forestry result in this being a complex site. Wakes from upstream turbines were detected and quantified using the downstream lidar wind flow complexity measurements. The paper will present the results of the wake measurement campaign and analysis. Finally, the lidars’ ability to wind measure flow complexity will be explored from the point of view of minimising Category A measurement uncertainty in turbine performance measurement.