A Novel Model-Free Predictive Control for T-Type Three-Level Grid-Tied Inverters

Zheng Yin, Cungang Hu, Kui Luo, Tao Rui, Zhuangzhuang Feng, Geye Lu and Pinjia Zhang
Additional contact information
Zheng Yin: School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
Cungang Hu: School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
Kui Luo: State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China
Tao Rui: School of Internet, Anhui University, Hefei 230601, China
Zhuangzhuang Feng: School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
Geye Lu: Department of Electrical Engineering, Tsinghua University, Beijing 100190, China
Pinjia Zhang: School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China

Energies, 2022, vol. 15, issue 18, 1-15

Abstract: The model-free predictive control (MFPC) scheme is an effective scheme to enhance the parameter robustness of model predictive control. However, the MFPC scheme can be affected by the current gradient updating frequency. This paper proposes an improved MFPC scheme for a T-type three-level inverter. First, a novel current gradient updating method is designed to estimate all current gradients per control period, which uses the current gradient relationship between different voltage vectors and eliminates the effect of current gradients updating stagnation. Moreover, a sector judgment method based on the current gradient is proposed. Redundant small vectors are accurately judged and the computational burden is greatly reduced. Finally, simulation and experimental comparisons on a T-type three-level inverter verify the effectiveness of the proposed MFPC scheme.

Keywords: model-free predictive control; T-type three-level inverter; current gradient; stagnation effect; sector judgment (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/18/6557/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/18/6557/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:18:p:6557-:d:909707

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().