A Model Predictive Control Strategy with Virtual Vectors Visualization Analysis for Grid-Connected Converter

A large filter inductance is required for the finite-control-set model predictive control (FCS-MPC) strategy of grid-connected converters (GCCs) to reduce current ripples and improve grid current quality, restricting the application of FCS-MPC for GCC. To solve this problem, a virtual vectors model predictive control strategy with visualization analysis for GCCs is proposed. This strategy evaluates the voltage errors of each sector through the design's visualization analysis method, and virtual vectors are designed at the locations where the voltage error is maximum. This helps to reduce the error between the actual current and the predicted one. As a result, it improves the accuracy of current prediction and reduces the filter inductance. The effectiveness of the proposed method is verified by comparative experiments with the conventional FCS-MPC strategy.