LAPSE:2023.27059
Published Article
LAPSE:2023.27059
Model Predictive Control for Virtual Synchronous Generator with Improved Vector Selection and Reconstructed Current
Nan Jin, Chao Pan, Yanyan Li, Shiyang Hu, Jie Fang
April 3, 2023
Due to the large-scale renewable energy connected to the power grid by power electronic converters, the inertia and stability of the power grid is declining. In order to improve the inertia and support the grid recovery, the three-phase converter works as a virtual synchronous generator (VSG) to respond to the frequency and voltage changes of the power grid. This paper proposes a model predictive control for the virtual synchronous generator (MPC-VSG) strategy, which can automatically control the converter output power with the grid frequency and voltage changes. Further consideration of fault-tolerant ability and reliability, the method based on improved voltage vector selection, and reconstructed current is used for MPC-VSG to ensure continuous operation for three-phase converters that have current-sensor faults, and improve the reconstruction precision. The proposed method can respond to the frequency and voltage changes of the power grid and has fault-tolerant ability, which is easy to realize without pulse width modulation (PWM) and a proportional-integral (PI) controller. The effectiveness of the proposed control strategy is verified by experiment.
Keywords
current reconstruction, Model Predictive Control, virtual synchronous generator, voltage vector
Suggested Citation
Jin N, Pan C, Li Y, Hu S, Fang J. Model Predictive Control for Virtual Synchronous Generator with Improved Vector Selection and Reconstructed Current. (2023). LAPSE:2023.27059
Author Affiliations
Jin N: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China [ORCID]
Pan C: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China
Li Y: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China
Hu S: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China [ORCID]
Fang J: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China
Journal Name
Energies
Volume
13
Issue
20
Article Number
E5435
Year
2020
Publication Date
2020-10-18
Published Version
ISSN
1996-1073
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PII: en13205435, Publication Type: Journal Article
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LAPSE:2023.27059
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doi:10.3390/en13205435
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