High-Fidelity Model Order Reduction for Microgrids Stability Assessment

• Published in: IEEE transactions on power systems 2018-01, Vol.33 (1), p.874-887
• Main Authors: Vorobev, Petr, Po-Hsu Huang, Al Hosani, Mohamed, Kirtley, James L., Turitsyn, Konstantin
• Format: Article
• Language: English
• Subjects: Computational modeling; Droop control; Inverters; Microgrids; Power system dynamics; Power system stability; Reduced order systems; reduced-order model; small-signal stability; Stability analysis
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2017.2707400

Proper modeling of inverter-based microgrids is crucial for accurate assessment of stability boundaries. It has been recently realized that the stability conditions for such microgrids are significantly different from those known for large-scale power systems. In particular, the network dynamics, despite its fast nature, appears to have major influence on stability of slower modes. While detailed models are available, they are both computationally expensive and not transparent enough to provide an insight into the instability mechanisms and factors. In this paper, a computationally efficient and accurate reduced-order model is proposed for modeling inverter-based microgrids. The developed model has a structure similar to quasi-stationary model and at the same time properly accounts for the effects of network dynamics. The main factors affecting microgrid stability are analyzed using the developed reduced-order model and shown to be unique for microgrids, having no direct analogy in large-scale power systems. Particularly, it has been discovered that the stability limits for the conventional droop-based system are determined by the ratio of inverter rating to network capacity, leading to a smaller stability region for microgrids with shorter lines. Finally, the results are verified with different models based on both frequency and time domain analyses.