  We consider the problem of dispatching WindFarm (WF) power demand to
individual Wind Turbines (WT) with the goal of minimizing mechanical stresses.
We assume wind is strong enough to let each WTs to produce the required power
and propose different closed-loop Model Predictive Control (MPC) dispatching
algorithms. Similarly to existing approaches based on MPC, our methods do not
require changes in WT hardware but only software changes in the SCADA system of
the WF. However, differently from previous MPC schemes, we augment the model of
a WT with an ARMA predictor of the wind turbulence, which reduces uncertainty
in wind predictions over the MPC control horizon. This allows us to develop
both stochastic and deterministic MPC algorithms. In order to compare different
MPC schemes and demonstrate improvements with respect to classic open-loop
schedulers, we performed simulations using the SimWindFarm toolbox for MatLab.
We demonstrate that MPC controllers allow to achieve reduction of stresses even
in the case of large installations such as the 100-WTs Thanet offshore WF.
