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Integrated Model Predictive Control of a Single-Phase Multilevel T-type Converter for a Photovoltaic Grid Connected System under Failure Conditions

Boudja Wassim, Barra Kamel

Power Electronics and Drives

2023

Vol. 8 (43)

142-164

The article presents two contributions: the first is an optimised control structure for photovoltaic grid connected systems (PVGCSs). The power chain is composed of two cascaded power converters, namely, a boost converter and a five-level T-type multilevel converter. Traditionally, each power converter is controlled by a separate mode control (SMC) from the other, which is computationally intensive since each converter requires its own control system, which is not practical. The suggested control, called integrated finite set model predictive control (IFS-MPC), allows controlling cascaded converters at the same time in one stage, instead of controlling them separately. Consequently, the overall implementation system is widely reduced. The second contribution of the article is a modified IFS-MPC called modified integrated finite set-model predictive control (M-IFS-MPC), which ensures the correct functioning of the grid-tied PV system under certain faults in converter components. Indeed, when one of the DC-link capacitors fails or when one of the auxiliary switches breaks down, by selecting an appropriate choice of the DC-link capacitors’ voltage reference, the proposed design allows a normal operation without intervention on the power circuit.

Model predictive control of NPC three-level grid-tied converter based on reconstructed current

Li Yanyan, Xiao Han, Jin Nan, Yan Guanglu

Archives of Electrical Engineering

2022

Vol. 71, nr 2

363--377

The neutral point clamped (NPC) three-level grid-tied converter is the key equipment connecting renewable energy and power grids. The current sensor fault caused by harsh environment may lead to the split of renewable energy. The existing sensor fault-tolerant methods will reduce the modulation ratio index of the converter system. To ensure continuous operation of the converter system and improve the modulation index, a model predictive control method based on reconstructed current is proposed in this paper. According to the relationship between fault phase current and a voltage vector, the original voltage vector is combined and classified. To maintain the stable operation of the converter and improve the utilization rate of DC voltage, two kinds of fault phase current are reconstructed with DC current, normal phase current and predicted current, respectively. Based on reconstructed three-phase current, a current predictive control model is designed, and a model predictive control method is proposed. The proposed method selects the optimal voltage vector with the cost function and reduces time delay with the current reconstruction sector. The simulation and experimental results show that the proposed strategy can keep the NPC converter running stably with one AC sensor, and the modulation index is increased from 57.7% to 100%.