4.6 Article Proceedings Paper

Adaptive Virtual Impedance-Based Reactive Power Sharing in Virtual Synchronous Generator Controlled Microgrids

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2020.3039223

关键词

Impedance; Reactive power; Microgrids; Voltage control; Resistance; Inverters; Frequency control; Adaptive virtual impedance; microgrids; reactive power sharing; surface curve fitting; virtual synchronous generator (VSG)

资金

  1. RDC Ignite RD Fund [5404-2059-101]

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The proposed adaptive virtual impedance-based VSG control approach aims to improve reactive power sharing among DGs in microgrids by alleviating impedance difference at inverter output. The virtual impedance consists of an adaptive virtual resistance and a fixed virtual inductance, designed adaptively based on microgrid operation points. The performance of the control system is demonstrated through simulation studies and validated against existing methods.
As a new emerging approach, virtual synchronous generator (VSG) control for interfacing inverters in renewable distributed generation (DG)-based microgrids has attracted significant research interest. However, VSG control cannot ensure proportional reactive power sharing among DG units when unequal transmission line impedances are involved, although active power sharing remains proportional among DGs. In this article, an adaptive virtual impedance-based VSG control approach for grid-connected and islanded microgrids is proposed to alleviate impedance difference at the inverter output and improve proportional reactive power sharing among DGs. The virtual impedance consists of an adaptive virtual resistance and a fixed virtual inductance, where the virtual resistance is designed adaptively based on operation points of the microgrid. In this article, the proposed adaptive virtual impedance control is implemented on a modified VSG control, known as fuzzy secondary controller-based VSG control, offering excellent voltage and frequency regulation at the PCC. Its performance is demonstrated through case and sensitivity studies using MATLAB/Simulink simulation; and further validated by comparing with an existing method.

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