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| Multi-Timescale Modeling and Dynamic Stability Analysis for Sustainable Microgrids: State-of-the-Art and Perspectives |
| Mingyue Zhang,Yang Han, Senior Member, IEEE,Yuxiang Liu,Amr S. Zalhaf,Ensheng Zhao,Karar Mahmoud,Mohamed M. F. Darwish,Frede Blaabjerg |
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| Abstract: |
| The increasing trend for integrating renewable energy sources into the grid to achieve a cleaner energy system is one of the main reasons for the development of sustainable microgrid (MG) technologies. As typical power-electronized power systems, MGs make extensive use of power electronics converters, which are highly controllable and flexible but lead to a profound impact on the dynamic performance of the whole system. Compared with traditional large-capacity power systems, MGs are less resistant to perturbations, and various dynamic variables are coupled with each other on multiple timescales, resulting in a more complex system in-stability mechanism. To meet the technical and economic challenges, such as active and reactive power-sharing, volt-age, and frequency deviations, and imbalances between power supply and demand, the concept of hierarchical control has been introduced into MGs, allowing systems to control and manage the high capacity of renewable energy sources and loads. However, as the capacity and scale of the MG system increase, along with a multi-timescale control loop design, the multi-timescale interactions in the system may become more significant, posing a serious threat to its safe and stable operation. To investigate the multi-timescale behaviors and instability mechanisms under dynamic inter-actions for AC MGs, existing coordinated control strategies are discussed, and the dynamic stability of the system is defined and classified in this paper. Then, the modeling and assessment methods for the stability analysis of multi-timescale systems are also summarized. Finally, an outlook and discussion of future research directions for AC MGs are also presented. |
| Key words: Sustainable microgrid, hierarchical control, modeling, model simplification, multi-timescale, dynamic stability analysis, timescale decomposition. |
| DOI：10.23919/PCMP.2023.000317 |
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| Fund:This work is partly supported by the National Natural Science Foundation of China (NSFC) (No.51977026), the Science and Technology Program of Sichuan Province (No.2021YFG0255), and the Sichuan Provincial Postdoctoral Science Foundation (No.246861) |
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