| 13 Feb 2026
Fast blockage models for wind-farm power prediction
Abstract. Large offshore wind farms can trigger atmospheric gravity waves, with the associated hydrostatic blockage effect impacting their energy yield. Unfortunately, to date no tools exist that can model this wind-farm gravity-wave interaction and blockage at a computational cost that is not drastically higher than conventional engineering wake models. To address this, this paper applies insights from two-scale momentum (2SM) theory to an atmospheric perturbation model (APM), thereby significantly speeding up the latter. This leads to two different models, with one using pre-computed farm-level coefficients to compute the turbine forces and power output, while the other relies on repeated wake model evaluations. The core 2SM hypothesis and both developed models are validated using a prior LES dataset of a large wind farm. Both fast 2SM—APMs perform well, predicting blockage-corrected farm power at a computational cost that is only a factor 40 slower than a standalone wake model.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.
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