Direct Instantaneous Ripple Power Predictive Control for Active Ripple Decoupling of Single-Phase Inverter Academic Article uri icon

abstract

  • © 1982-2012 IEEE. Active ripple decoupling technique of the single-phase inverter is a popular topic to minimize the dc-link capacitance. However, the existing control methods are based on tracking sinusoidal or predetermined voltage waveforms of the compensation capacitor, assuming the inverter outputs are pure sinusoidal voltage and current. Therefore, the performance of existing methods degrades when the inverter output voltage and current are not purely sinusoidal. Furthermore, the limited dynamic performance threatens the safety of dc-link capacitor when the load changes. This happens, because the inrush ripple power is injected into dc link with small capacitance and the dc-link voltage will suddenly rise up when the ripple power is not buffered during transients. In this paper, a direct instantaneous power predictive control is proposed for the decoupling circuit to buffer ripple power of the single-phase inverter, which combines instantaneous ripple power control with model predictive control to overcome the issues above. The proposed method tracks the instantaneous ripple power rather than voltage or current waveforms. In this way, it can fully buffer all ripple powers in the system even for distorted output voltage and current of the inverter and enables the full utilization of storage capacitor. In addition, model predictive control makes the proposed method have fast dynamic and perfectly compensate ripple power during transients and steady states. The buck-type active ripple decoupling circuit is chosen to implement the proposed method after comparing with another typical decoupling topology. The proposed method is also compared with conventional method using proportional-integral-resonant regulator to track the predetermined capacitor voltage waveform. Experimental tests verify the theoretical analysis and the proposed control method.

author list (cited authors)

  • Ge, B., Li, X., Zhang, H., Liu, Y., Balog, R. S., Abu-Rub, H., & Alpuerto, L.

citation count

  • 30

publication date

  • January 2018