Supplying Three Phase, Four Wire, Unbalanced and Non-Linear, Asymmetric Ohmic-Inductive Load by NPC Inverter Based on Method Predictive Control

Document Type: Original Research Paper


1 Department of Electrical Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran

2 Department of Electrical Engineering, East Tehran Branch, Islamic Azad University, Tehran, Iran

3 Department of Electrical and Computer Engineering, University of Mohaghegh Ardabili, Ardabil, Iran


In this paper, unbalanced, nonlinear and asymmetric ohmic-inductive three-phase load are supplied by the NPC inverter based on the model named Model Predictive Control (MPC). The MPC is designed for the compensator. The basic principles of MPC as well as MPC model are described in this paper. The design of the proposed controller along with the MPC control steps for controlling the power converter and modeling the power converter are provided to determine all possible switching conditions. Also, the cost function that describes the optimal behavior of the system is formulated. Further, discrete models are defined when future behavior predicts controlled variables. Then the switching modes of the NPC inverter are presented and the control scheme is described based on the control schema for the MPCs with the purpose of power converters and drives, variables prediction and cost function definition. The system performance is evaluated based on the proposed method in various loads including symmetric load and symmetric reference flow, unbalanced load, and symmetric phase voltage. The simulation results indicate the optimal performance of the proposed method in supplying three-phase load demand with optimal quality so that the current distortion is low and the inverter output voltage is also multi-level. In addition, considering asymmetric ohmic-inductive loadand step variation in load, the harmonic distortion of the flow is 0.5% in a phase and the output voltage of inverter is also extracted multilevel. The best advantage of the proposed approach compared to SVM methods is controlling without the use of 3D Space Vector. This makes it easier to compute and implement easier than the 3D-SVM.


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