Optimal control of variable-speed wind turbines modeled as Markov jump systems

Abstract

This paper shows the solution for the control problem of operating wind turbines through Markov jump nonlinear systems. The idea is to represent wind speed acting on the turbine blades into modes of Markov chain. The main result then characterizes the optimal control for the long-run average cost of turbine operation. As a byproduct, the turbine model becomes second-moment stable, a concept borrowed from the literature of stochastic systems. To illustrate the benefits of our approach, we performed simulations in the FAST 5-MW wind turbine; the simulated data suggest that our control outperform other control strategies from the literature—increasing the produced power by 0.53%.