An economic model predictive control approach using convex optimization for wind turbines

Cost reduction of wind power motivates the development of advanced control algorithms to enhance both efficiency and reliability of wind turbines. Achieving this goal can be done through maximizing wind energy capture while mitigating turbine fatigue loads. In this paper, an economic model predictive control framework is presented to achieve the aforementioned goal. A convex formulation of the optimal control problem is adopted within the model predictive control framework, thus yielding a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control framework is compared to that of a baseline controller, which is widely used as a benchmark for evaluating new control algorithms. Simulation results show the ability of the proposed controller to reduce tower fatigue load with no or minimal impact on energy capture.