A new optimal model predictive control scheme for a wind energy conversion system

Abstract

AbstractThe correct management of power exchange between the doubly‐Fed induction generator (DFIG) and the grid depends on the effective optimal operation of the DFIG based wind energy conversion system (WECS). A modified optimal model predictive controller (MPC) architecture for WECS is proposed in this paper. The proposed scheme is carried out in two stages, as follows: (a) Using the MPC model and the tracking factor, an optimal control law is created, and (b) the aforementioned optimized issue is addressed using the linear matrix inequality (LMI) approach. Some improvements were made to the conventional LMI‐based MPC technique to lower the high computational complexity. To perform active and reactive power control in DFIG, the proposed approach is applied on the rotor‐side converter (RSC) control. The control law is divided into two sections. The first section deals with rotor current, while the second section deals with the RSC switching states. The LMI is used in the second portion of the control law to find the best switching state solution. The proposed method was created using the MATLAB/SIMULINK environment and tested in a 1hP DFIG‐WECS setup. By comparing the obtained results to conventional LMI‐PI, MPC‐based WECS, the effectiveness of the obtained results is verified. Variable wind speed conditions are used to vary all the results. Integral absolute error, integral time absolute error, and Integral square error measurements are used to compare the tracking performance index of all methods.