Stochastic wind farm flow generation using a reduced order model of LES

Abstract Large eddy simulations are computationally expensive, which typically limits the simulation time and hence statistics useful for validation. Here, a reduced order model with stochastic engine is used to generate inflow 48 wind turbines in Lillgrund farm. The flow realization captures power production more importantly correct cross-correlations blade root flapwise bending moments over large spatiotemporal region, farm covers. analysis show how cross-correlation increase further into farm, where highly turbulent becomes increasingly self-organized dynamic interaction across entire captured by first eight modes. Overall, dynamics at fraction of computational cost, effectively generalizing LES results beyond relatively short period.