Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/29068
Title: | Improving Stability of Low-Inertia Systems using Virtual Induction Machine Synchronization for Grid-Following Converters | Authors: | Stanojev, Ognjen Markovic, Uros Aristidou, Petros Hug, Gabriela |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Voltage source converter;Induction machine;Phase-locked loop;Self-synchronization;Virtual inertia emulation | Issue Date: | 1-Jul-2022 | Source: | IEEE Transactions on Power Systems, 2022 | Journal: | IEEE Transactions on Power Systems | Abstract: | This paper presents a novel strategy for the synchronization of grid-following Voltage Source Converters (VSCs) in power systems with low rotational inertia. The proposed synchronization unit is based on emulating the physical properties of an induction machine and capitalizes on its inherent grid-friendly properties such as self-synchronization, oscillation damping, and standalone capabilities. To this end, the mathematical model of an induction machine is analyzed and reformulated to obtain the unknown grid frequency by processing the voltage and current measurements at the converter output. This eliminates the need for a Phase-Locked Loop (PLL) unit, traditionally employed in grid-following VSC control schemes, while simultaneously preserving the system- and device-level control. Furthermore, we provide the appropriate steps for obtaining an index-1 DAE representation of the induction-machine-based synchronization unit, suitable for stability analysis. Our analysis shows that replacing the PLL unit with the virtual induction machine-based synchronization may considerably improve the stability of systems with grid-following converters and facilitate the frequency containment. Furthermore, we validate the performance of the proposed synchronization unit through simulations and provide recommendations for its tuning. | URI: | https://hdl.handle.net/20.500.14279/29068 | ISSN: | 15580679 | DOI: | 10.1109/TPWRS.2022.3187789 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Article | Affiliation : | Cyprus University of Technology Swiss Federal Institute of Technology ETH Zurich |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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2022JStanojev.pdf | 4.38 MB | Adobe PDF | View/Open |
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