By coupling large-eddy simulation (LES) codes to weather data from large-scale models, previous studies showed the viability of “real-weather” LES. However, when simulating extended periods (up to one year) of weather, a number of them diagnosed an underestimation of the simulated temporal spectrum (of wind and solar irradiance) at timescales of a few hours (i.e., the atmospheric mesoscale). This study presents simulations aimed at reproducing the observed wind spectrum from timescales of one year to one minute, including the mesoscale. Reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis Version 5) are used as boundary conditions to a mesoscale simulation with either a local or a non-local formulation of vertical diffusion, which then drives an LES (resolution of 50 m). Several domain sizes are used to simulate the weather during 2022 over a meteorological tower in The Netherlands. It is shown that, when increasing the size of the mesoscale simulation from 64 km to 1024 km, the LES wind spectrum at the mesoscale approaches the observed spectrum. The spectrum is also sensitive to the mesoscale diffusion formulation, which either resolves or suppresses explicit convection, resulting in a different LES wind spectrum. In addition, it is shown that the higher order statistics (structure functions) improve by using a large enough mesoscale simulation. The results indicate that LES can be used as a tool to simulate the temporal dynamics of the wind at all timescales between one minute and one year, if the atmospheric mesoscales are taken into account appropriately.

As a consequence of the rapid growth of the globally installed offshore wind energy capacity, the size of individual wind farms is increasing. This poses a challenge to models that predict energy production. For instance, the current generation of wake models has mostly been calibrated on existing wind farms of much smaller size. This work analyzes annual energy production and wake losses for future, multi-gigawatt wind farms with atmospheric large-eddy simulation. To that end, 1 year of actual weather has been simulated for a suite of hypothetical 4 GW offshore wind farm scenarios. The scenarios differ in terms of applied turbine type, installed capacity density, and layout. The results suggest that production numbers increase significantly when the rated power of the individual turbines is larger while keeping the total installed capacity the same. Even for turbine types with similar rated power but slightly different power curves, significant differences in production were found. Although wind speed was identified as the most dominant factor determining the aerodynamic losses, a clear impact of atmospheric stability and boundary layer height has been identified. By analyzing losses of the first-row turbines, the yearly average global-blockage effect is estimated to between 2 and 3 %, but it can reach levels over 10 % for stably stratified conditions and wind speeds around 8 m s−1. Using a high-fidelity modeling technique, the present work provides insights into the performance of future, multi-gigawatt wind farms for a full year of realistic weather conditions.