  The current trend in the evolution of wind turbines is to increase their
rotor size in order to capture more power. This leads to taller, slender and
more flexible towers, which thus experience higher dynamical loads due to the
turbine rotation and environmental factors. It is hence compelling to deploy
advanced control methods that can dynamically counteract such loads, especially
at tower positions that are more prone to develop cracks or corrosion damages.
Still, to the best of the authors' knowledge, little to no attention has been
paid in the literature to load mitigation at multiple tower locations.
Furthermore, there is a need for control schemes that can balance load
reduction with optimization of power production. In this paper, we develop an
Economic Model Predictive Control (eMPC) framework to address such needs.
First, we develop a linear modal model to account for the tower flexural
dynamics. Then we incorporate it into an eMPC framework, where the dynamics of
the turbine rotation are expressed in energy terms. This allows us to obtain a
convex formulation, that is computationally attractive. Our control law is
designed to avoid the 'turn-pike' behavior and guarantee recursive feasibility.
We demonstrate the performance of the proposed controller on a 5MW reference WT
model: the results illustrate that the proposed controller is able to reduce
the tower loads at multiple locations, without significant effects to the
generated power.
