Parameter-free predictive control with flexibility in power adjustment for grid-connected converters under unbalanced grid conditions

This paper introduces a novel finite control set predictive direct power control method for grid-connected converters without cost function evaluations. Unlike conventional predictive direct power control, since the proposed method does not use the model parameters, their uncertainties do not cause prediction error and inappropriate voltage vector selection. The method employs a new form of voltage vector selection based on the slopes of active and reactive powers. The slopes are predicted in a manner with a low sensitivity to sampling noise, without updating a look-up table, and recursive methods. Hence, there are no stagnation and convergence issues. Also, the proposed method avoids startup problems caused by data-lacking due to directly regulating the active and reactive power by a switching logic. Flexible power oscillations control with balanced sinusoidal grid currents without any signal sequence extraction can also be achieved under this method in unbalanced grid conditions. The proposed method is assessed by both simulation and experimental studies, and its performance is compared with existing robust combined and model predictive control methods. The outcomes highlight the influence of the proposed approach and establish its superiority over the other considered methods. Proposing a parameter-less predictive control addressing sampling noises and startup problems.Directly selects the optimal voltage vector to lower the computational burden of the predictive control method.Directly selects the optimal voltage vector to lower the computational burden of the predictive control method.Excludes the positive and negative sequence extraction of grid voltage and currents within the control structure. image