Model Predictive Control of Multi-Level Neutral Point Clamp (NPC) Grid-Connected Inverter Using Power Block Geometry (PBG) Approach

In a grid connected renewable energy systems, where multiple DC power sources supply current to the grid, controlling the injected current is an important issue. When considering renewable energy resources, such as photovoltaic (PV), multi-level converters are needed to convert the DC power to AC power suitable for the grid with less harmonic distortion. Since different sources may have different power delivery levels model predictive control (MPC) is proposed to control the neutral-point clamp (NPC) inverter to regulate the injected power to the grid. Further, since there are numerous power electronics converters topologies used to solve this problem the power block geometry (PBG) is proposed to facilitate the analysis of multi-level converters and the design of MPC controller. This paper presents a model-predictive control-based on power block geometry method, single-phase and three-phase NPC inverters based MPC are simulated in MATLAB, to control the injected current into the grid. The power block geometry speeds up both analysis of the four-level NPC inverter and the MPC design since it is based on geometrical representation with specific rules that establishes a formation law.