Posters

Abstract

Atmospheric stability describes the tendency of the atmosphere to suppress or enhance vertical motion of air, determined by the temperature profile of the atmosphere. The atmospheric stability is known to influence wind flow, turbulence, and wind turbine wakes. The impact of these conditions is not currently captured by most industry standard engineering wake models. Atmospheric stability conditions can be classified in several ways, including Monin-Obukhov Length (MOL) and the Bulk Richardson number. These parameters can be derived from on-site measurements where available, and from reanalysis datasets such as ERA5. Several methods exist for quantifying wake losses from operational data, including the data binning approach for the single-wake situation, the individual model (IND) and the Gaussian Markov Random Field (GMRF) model for heterogenous wake effects. This study examines the wake losses of two operational on-shore wind farms, using the open datasets, Kelmarsh and Penmanshiel. Atmospheric stability conditions throughout the data period are derived from ERA5 reference data, and the operational data is grouped by atmospheric stability class. The wake losses are then estimated for each group to quantify the variation due to the atmospheric stability. The results are then compared against typical engineering wake models, including the Jenson model and the Eddy Viscosity model, which assume neutral atmospheric conditions. Other datasets may be added pending approval from the owners.