Model predictive control for wind power generation smoothing with controlled battery storage

The aim of this study is to design a controller based on model predictive control (MPC) theory to smooth wind power generation along with the controlled storage of the wind energy in batteries in presence of variety of constraints. In this study, a proposed wind power prediction system is utilized to optimize the performance of the controller. The proposed controller is capable of smoothing wind power by utilizing the inputs from our prediction system which in turn optimizes the maximum ramp rate requirement. At the same time this controller optimizes the state of charge of battery under practical constraints. The prediction model involved is capable of predicting wind power multi-step ahead which are used in the optimization part of the controller. The proposed system is tested for different scenarios and under variety of hard constraints. The effectiveness of our proposed model is shown by simulation results.