A Three-Level Inverter-Based Model Predictive Control Design for Optimal Wind Energy Systems

This paper proposes, an innovative model predictive control strategy for a grid-connected wind energy system using a three-level inverter. The method features a command structure with a single DC/AC multilevel three-phase inverter, which significantly decreases the number of converters required, thereby reducing the system design costs in comparison to the traditional back-to-back configuration that requires both DC/AC and AC/DC converters. The inverter is modelled discretely at the synchronous reference frame with a discrete-time prediction for future direct and quadrature components of the grid current and DC-link capacitor voltages. The controller evaluates each possible switching state of the inverter with a cost function and chooses the state that minimizes this cost for realization during the next sampling period. The proposed approach is verified using a processor-in-the-loop methodology along with a software simulation. The results show that this approach optimizes wind power generation and enhances the energy quality injected into the grid, as indicated by the lower total harmonic distortion

Keywords: Model predictive control, multilevel NPC inverter, wind energy, maximum power point Tracking.