A new model predictive control algorithm by reducing the computing time of cost function minimization for NPC inverter in three-phase power grids. (November 2017) - Taheri, Asghar; Zhalebaghi, Mohammad Hadi
Abstract: This paper presents a new control strategy based on finite-control-set model-predictive control (FCS-MPC) for Neutral-point-clamped (NPC) three-level converters. Containing some advantages like fast dynamic response, easy inclusion of constraints and simple control loop, makes the FCS-MPC method attractive to use as a switching strategy for converters. However, the large amount of required calculations is a problem in the widespread of this method. In this way, to resolve this problem this paper presents a modified method that effectively reduces the computation load compare with conventional FCS-MPC method and at the same time does not affect on control performance. The proposed method can be used for exchanging power between electrical grid and DC resources by providing active and reactive power compensations. Experiments on three-level converter for three Power Factor Correction (PFC), inductive and capacitive compensation modes verify the good and comparable performance. The results have been simulated using MATLAB/SIMULINK software. Highlights: An algorithm based on finite-control-set model-predictive control (FCS-MPC). using a simple procedure to decrease the processing time considerably. The proposed approach can be applied to multi-level inverters and suitably can accept the various constraints. Good performance in dynamic response, quality of load current, and balance of DC-link capacitors.