Turbine- and farm-scale power losses in wind farms: an alternative to wake and farm blockage losses

Turbine–wake and farm–atmosphere interactions can reduce wind farm power production. To model farm performance, it is important to understand the impact of different flow effects on the farm efficiency (i.e. farm power normalised by the power of the same number of isolated turbines). In this study we analyse the results of 43 large-eddy simulations (LESs) of wind farms in a range of conventionally neutral boundary layers (CNBLs). First, we show that the farm efficiency η_f is not well correlated with the wake efficiency η_w (i.e. farm power normalised by the power of front-row turbines). This suggests that existing metrics, classifying the loss of farm power into wake loss and farm blockage loss, are not best suited for understanding large wind farm performance. We then evaluate the assumption of scale separation in the two-scale momentum theory (Nishino and Dunstan, 2020) using the LES results. Building upon this theory, we propose two new metrics for wind farm performance: turbine-scale efficiency η_TS, reflecting the losses due to turbine–wake interactions, and farm-scale efficiency η_FS, indicating the losses due to farm–atmosphere interactions. The LES results show that η_TS is insensitive to the atmospheric condition, whereas η_FS is insensitive to the turbine layout. Finally, we show that a recently developed analytical wind farm model predicts η_FS with an average error of 5.7 % from the LES results.