A Decentralized Current-Sharing Controller Endows Fast Transient Response to Parallel DC-DC Converters - 2017


This paper proposes a decentralized current-sharing management strategy to endow quick transient response to paralleled dc-dc converters systems, like dc microgrids or distributed power systems. The proposed controller encompass 2 main management loops: an external voltage droop management for current-sharing proposes and an interior current loop. The external droop control loop is intended as a voltage loop with embedded virtual impedance, that avoids the use of a slow voltage loop and a separate extra virtual impedance loop which will limit the system bandwidth. The internal current loop, thanks to the external control loop simplification, plays a significant role within the system bandwidth, so that an adaptive proportional-integral (PI) controller is proposed for this matter. Within the paper, 2 totally different droop management strategies are modeling, designed, simulated, and tested: The conventional virtual-impedance-loop based V-I droop and therefore the proposed embedded-virtual-impedance based mostly I-V droop. So as to match the dynamic response performances between 2 droop controllers, their state-house models have been developed and analyzed in this paper. The results show that the dynamic response of the I-V droop management is faster than that of the traditional V-I droop management. Furthermore, by analyzing the consequences from I-V droop control parameters, the errors can be reduced faster by enlarging the proportional terms, however with no fluctuations, and then utterly eliminated by restoring back to tiny proportional values. Meanwhile, there exists a tradeoff phenomenon between the fast dynamic response and smart steady-state performance; so, an adaptive PI controller is proposed to both improve dynamic response and guarantee good steady-state performance simultaneously. Experimental results are shown to verify the accuracy of the models and the effectiveness of the proposed control framework.

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