Advanced System-Level Model Reduction Method for Multi-Converter DC Power Systems

For dynamic stability analysis and instability mechanism understanding of multi-converter medium voltage DC power systems with droop-based double-loop control, an advanced system-level model reduction method is proposed. With this method, mathematical relationships of control parameters (e.g., curre...

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Vydáno v:CSEE Journal of Power and Energy Systems Ročník 10; číslo 4; s. 1550 - 1562
Hlavní autoři: Lin Zhu, Xueshen Zhao, Xialin Li, Li Guo, Bo Zhao, Zhanfeng Deng, Hao Lu, Chengshan Wang
Médium: Journal Article
Jazyk:angličtina
Vydáno: China electric power research institute 01.07.2024
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ISSN:2096-0042, 2096-0042
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Shrnutí:For dynamic stability analysis and instability mechanism understanding of multi-converter medium voltage DC power systems with droop-based double-loop control, an advanced system-level model reduction method is proposed. With this method, mathematical relationships of control parameters (e.g., current and voltage control parameters) between the system and its equivalent reduced-order model are established. First, open-loop and closed-loop equivalent reduced-order models of current control loop considering dynamic interaction among converters are established. An instability mechanism (e.g., unreasonable current control parameters) of the system can be revealed intuitively. Theoretical guidance for adjustment of current control parameters can also be given. Then, considering dynamic interaction of current control among converters, open-loop and closed-loop equivalent reduced-order models of voltage control loop are established. Oscillation frequency and damping factor of DC bus voltage in a wide oscillation frequency range (e.g., 10–50 Hz) can be evaluated accurately. More importantly, accuracy of advanced system-level model reduction method is not compromised, even for MVDC power systems with inconsistent control parameters and different number of converters. Finally, experiments in RT-BOX hardware-in-the-loop experimental platform are conducted to validate the advanced system-level model reduction method.
ISSN:2096-0042
2096-0042
DOI:10.17775/CSEEJPES.2021.08530