LAPSE:2023.23274
Published Article
LAPSE:2023.23274
Improved Predictive Control in Multi-Modular Matrix Converter for Six-Phase Generation Systems
Sergio Toledo, Edgar Maqueda, Marco Rivera, Raúl Gregor, Pat Wheeler, Carlos Romero
March 27, 2023
Distributed generation systems are emerging as a good solution as part of the response to the world’s growing energy demand. In this context multi-phase wind generation systems are a feasible option. These systems consist of renewable AC sources which requires efficient and controlled power conversion stages. This work proposes a novel predictive current control strategy that takes advantage of a multi-modular matrix converter topology in the power stage of a six-phase generation system. The proposed method uses a coupling signal between the modules to decrease the error and the total harmonic distortion compared to independent control of each module. Experimental results validate the new control strategy showing the improvement regarding the target parameters.
Keywords
Model Predictive Control, modular matrix converter, multi-phase wind generation systems
Suggested Citation
Toledo S, Maqueda E, Rivera M, Gregor R, Wheeler P, Romero C. Improved Predictive Control in Multi-Modular Matrix Converter for Six-Phase Generation Systems. (2023). LAPSE:2023.23274
Author Affiliations
Toledo S: Facultad de Ingeniería, Universidad de Talca, Curicó 3341717, Chile; Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay [ORCID]
Maqueda E: Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay
Rivera M: Facultad de Ingeniería, Universidad de Talca, Curicó 3341717, Chile [ORCID]
Gregor R: Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay
Wheeler P: Faculty of Engineering, University of Nottigham, Nottingham NG7 2RD, UK [ORCID]
Romero C: Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay
Journal Name
Energies
Volume
13
Issue
10
Article Number
E2660
Year
2020
Publication Date
2020-05-25
Published Version
ISSN
1996-1073
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Original Submission
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PII: en13102660, Publication Type: Journal Article
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LAPSE:2023.23274
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doi:10.3390/en13102660
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Mar 27, 2023
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