Efficient stochastic wake modeling for wind farm control

Recent research into wind farm control promises the ability to create more densely populated wind farms and improved power production of existing wind farms by controlling for wake interactions between turbines. In this paper, a computationally efficient Discrete time Stochastic and Dynamic model (DStoDyn) is developed using of a wide sense stationary random variable with deterministic mean to model wind direction uncertainties in a wind farm. Comparisons to results obtained from the large eddy simulation software SOWFA show that general wake displacement trends may be represented by DStoDyn.