Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden
This paper proposes a novel dual-vector model predictive control (DV-MPC) method applied to modular multilevel converter(MMC). The traditional predictive control method generally aims to minimize the output current tracking error at the next sampling instant, while the proposed method minimizes the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10443368/ |
| _version_ | 1827339999955124224 |
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| author | Weifeng Zhang Jingwei Zhang Qiang Wang Yizhan Jiang Guojun Tan |
| author_facet | Weifeng Zhang Jingwei Zhang Qiang Wang Yizhan Jiang Guojun Tan |
| author_sort | Weifeng Zhang |
| collection | DOAJ |
| description | This paper proposes a novel dual-vector model predictive control (DV-MPC) method applied to modular multilevel converter(MMC). The traditional predictive control method generally aims to minimize the output current tracking error at the next sampling instant, while the proposed method minimizes the total harmonic distortion (THD) of the output current by quantifying the relationship between the THD and the output current trajectory within the next sampling period. The control of the circulating current is achieved by selecting proper total number of inserted submodules (SMs) in the upper and lower arms. By selecting appropriate SMs to insert or bypass, the voltage balance between submodules within the arm is fulfilled. This method accomplishes multiple control objectives without the need for cumbersome weighting factor design. At the same time, the adopted preselection method and total number of SMs selection method effectively reduce the calculation burden. Simulation and experimental results verify the superiority of the proposed method. |
| first_indexed | 2024-03-07T20:10:41Z |
| format | Article |
| id | doaj.art-386f1f21862045eaa02035ee77bf2528 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-07T20:10:41Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-386f1f21862045eaa02035ee77bf25282024-02-28T00:00:56ZengIEEEIEEE Access2169-35362024-01-0112285202853010.1109/ACCESS.2024.335964010443368Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation BurdenWeifeng Zhang0https://orcid.org/0000-0003-4392-9728Jingwei Zhang1https://orcid.org/0000-0002-3583-8386Qiang Wang2https://orcid.org/0000-0002-5157-8801Yizhan Jiang3https://orcid.org/0009-0004-4661-2894Guojun Tan4https://orcid.org/0000-0002-7888-9634School of Electrical Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou, ChinaThis paper proposes a novel dual-vector model predictive control (DV-MPC) method applied to modular multilevel converter(MMC). The traditional predictive control method generally aims to minimize the output current tracking error at the next sampling instant, while the proposed method minimizes the total harmonic distortion (THD) of the output current by quantifying the relationship between the THD and the output current trajectory within the next sampling period. The control of the circulating current is achieved by selecting proper total number of inserted submodules (SMs) in the upper and lower arms. By selecting appropriate SMs to insert or bypass, the voltage balance between submodules within the arm is fulfilled. This method accomplishes multiple control objectives without the need for cumbersome weighting factor design. At the same time, the adopted preselection method and total number of SMs selection method effectively reduce the calculation burden. Simulation and experimental results verify the superiority of the proposed method.https://ieeexplore.ieee.org/document/10443368/Current THDdual-vector model predictive controlmodular multilevel convertercalculation burden reduction |
| spellingShingle | Weifeng Zhang Jingwei Zhang Qiang Wang Yizhan Jiang Guojun Tan Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden IEEE Access Current THD dual-vector model predictive control modular multilevel converter calculation burden reduction |
| title | Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden |
| title_full | Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden |
| title_fullStr | Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden |
| title_full_unstemmed | Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden |
| title_short | Dual-Vector Model Predictive Control for Modular Multilevel Converter With Low Calculation Burden |
| title_sort | dual vector model predictive control for modular multilevel converter with low calculation burden |
| topic | Current THD dual-vector model predictive control modular multilevel converter calculation burden reduction |
| url | https://ieeexplore.ieee.org/document/10443368/ |
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