Robust Finite Control-Set Model Predictive Control for Power Quality Enhancement of a Wind System Based on the DFIG Generator

For many academics, it has proven difficult to operate a wind energy conversion system (WECS) under changeable speed while also enhancing the quality of electricity delivered grid. In order increase effectiveness and performance DFIG-based Wind Energy Conversion System, this research suggests an updated model predictive control technique. This study intends regulate generator in two ways: first, follow reference with high precision using rotor side grid converters; second, reduce error. The suggested approach optimizes value function current magnitude errors based on discrete mathematical forecast converter’s switching state. system, converter states are used directly as inputs. Thus, may be immediately subjected improved action. key advantage strategy over FCS-MPC methods is error reduction. originality proposal cost that allows for both successful results computation time minimization. To achieve this, first presented, followed by description control, then method applied control. demonstrate efficacy robustness technique, random profile was examine system’s unitary power factor. done compare other controls have been reported literature. simulation results, which were conducted 1.5 kW DFIG MATLAB/Simulink environment, technique highly effective terms speed, accuracy, stability, output ripple.