Distributed model predictive control of wind and solar generation system

Distributed model predictive control for a hybrid system that comprises wind and photovoltaic generation subsystems, a battery bank and an AC load is developed in this paper. Consider that the wind subsystem and the solar subsystem are two spatial distributed energy generation systems, so we design a distributed MPC for optimal management and operation of distributed wind and solar energy generation system. The wind and solar generation system is characterized by nonlinearity. Therefore, neural model is used to approximating the dynamics of nonlinear process. Reasonable solution to the optimization and constraints by using distributed model predictive control is presented. The performance of the distributed model predictive control is show through computer simulation to illustrate the advantages of the proposed method.

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