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Neutral Point Clamped (NPC) converters with n levels are traditionally controlled in such a way that the DC-link capacitors operate at 1/( n - 1) of the total DC-link voltage level. The voltage level across the DC-link capacitors has to be properly regulated by the capacitor unbalance control to contain the harmonic distortion of the converter output voltages. State-of-the-art modulation techniques address the problem of the DC-link voltage regulation for NPC inverters. However, they highly show reduced performance when unbalanced DC-link voltages are considered. In this paper, a novel Space Vector Modulation (SVM) is proposed for NPC converters with an unbalanced DC-link. At every modulation interval, the technique defines the optimal switching pattern by considering the actual unbalanced DC-link conditions. The proposed modulation allows improving the harmonic content of the NPC converter output voltage with respect to a traditional ML-SVM, when the same operating conditions are considered. As an extension, the proposed modulation technique will guarantee the same output voltage quality of a traditional ML-SVM with unbalanced DC-link, while improving the conversion efficiency thanks to a reduction of switching frequency.

The performance of Voltage Source Inverter (VSI) is affected by power semiconductor nonlinearities, dead time, and control delay. The compensation of these nonlinear effects is necessary to meet requirements in terms of current quality and high efficiency, especially for grid-connected power conversion systems. In this paper, the effects of nonlinearities are widely analyzed and a new compensation technique for a steady-state current-controlled VSI is proposed. It is based on a step-by-step voltage compensation on the basis of the current error evaluated within each control interval. As a result, a complete compensation is achieved within a whole period of the fundamental. To cope with the zero-current clamping effect, the proposed compensation technique is implemented in a recursive way. For slow-dynamic applications, such as photovoltaic systems, this method allows achieving high performance with very low computational requirements.