Finite-Control-Set Model Predictive Control for DFIG Wind Turbines

This paper presents a time efficient finite-control-set model predictive control (FCS-MPC) scheme for the doubly fed induction generator system. In this scheme, the switching states of the rotor side converter are directly taken as control inputs. This way, the optimized control action can be directly applied to the converter. Compared with the existing FCS-MPC approaches, the salient feature of the proposed scheme is the reduction of the computation time. By introducing a set of augmented decision variables, the original intractable binary quadratic programming problem in FCS-MPC can be analytically transformed to a binary linear programming problem, which can be solved efficiently. By this means, the computation time of the proposed scheme is much less than that of the existing schemes. This reduction in computation time enables FCS-MPC with longer prediction horizons, thus yielding better control performance.