Control Strategies for Islanded Microgrid Using Enhanced Hierarchical Control Structure With Multiple Current-Loop Damping Schemes

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Abstract
In this paper, the modeling, controller design, and stability analysis of the islanded microgrid (MG) using enhanced hierarchical control structure with multiple current loop damping schemes is proposed. The islanded MG consists of the parallel-connected voltage source inverters using inductor-capacitor-inductor (LCL) output filters, and the proposed control structure includes the primary control with additional phase-shift loop, the secondary control for voltage amplitude and frequency restoration, the virtual impedance loops which contain virtual positive- and negative-sequence impedance loops at fundamental frequency and virtual variable harmonic impedance loop at harmonic frequencies, and the inner voltage and current loop controllers. A small-signal model for the primary and secondary controls with additional phase-shift loop is presented, which shows an over-damped feature from eigenvalue analysis of the state matrix. The moving average filter-based sequence decomposition method is proposed to extract the fundamental positive and negative sequences and harmonic components. The multiple inner current loop damping scheme is presented, including the virtual positive, virtual negative, and variable harmonic sequence impedance loops for reactive and harmonic power sharing purposes, and the proposed active damping scheme using capacitor current feedback loop of the LCL filter, which shows enhanced damping characteristics and improved inner-loop stability. Finally, the experimental results are provided to validate the feasibility of the proposed approach.
Funding Information
  • National Natural Science Foundation of China (51307015)
  • State Key Laboratory of Power Transmission Equipment and System Security and New Technology (2007DA10512713405)
  • Open Research Subject of Sichuan Province Key Laboratory of Power Electronics Energy-Saving Technologies and Equipment (szjj2015-067)
  • Open Research Subject of Artificial Intelligence Key Laboratory of Sichuan Province (2015RZJ02)

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