Abstract
In order to solve the problem of weighting factors selection in the conventional finite-control-set model predictive control for a grid-connected three-level inverter, an improved multi-objective model predictive control without weighting factors based on hierarchical optimization is proposed. Four control objectives are considered in this strategy. The grid current and neutral-point voltage of the DC-link are taken as the objectives in the first optimization hierarchy, and by using fuzzy satisfaction decision, several feasible candidates of voltage vectors are determined. Then, the average switching frequency and common-mode voltage are optimized in the second hierarchy. The average ranking criterion is introduced to sort the objective functions, and the best voltage vector is obtained to realize the coordinated control of multiple objectives. At last, the effectiveness of the proposed strategy is verified by simulation results.
Highlights
Introduction1The grid-connected inverter is widely used as an important link between renewable energy and the power grid [1,2]
In order to solve the problem of weighting factors selection in the conventional finite-control-set model predictive control for a grid-connected three-level inverter, an improved multi-objective model predictive control without weighting factors based on hierarchical optimization is proposed
Their cost functions under candidate voltage vectors obtained from the first hierarchy are calculated, and the optimal voltage vector is selected according to the average ranking criterion of the objectives
Summary
The grid-connected inverter is widely used as an important link between renewable energy and the power grid [1,2]. The finite-control-set model predictive control (FCS-MPC) is one of the main control technologies for grid-connected inverters [5,6] In this technique, based on the discrete prediction model and the cost function of the control objective, an optimal. [13], the weighting factors are clearly derived based on the analytical expression of torque ripple This method relies heavily on model accuracy and cannot optimize the switching frequency simultaneously. A multi-objective model predictive control for grid-connected three-level inverter based on hierarchical optimization is proposed. Compared to the conventional FCS-MPC method, the proposed scheme solves the difficulty of designing the weighting factors of multi-objective predictive control.
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