EconPapers    
Economics at your fingertips  
 

Performance Comparisons of Three-Phase/Four-Wire Model Predictive Control-Based DC/AC Inverters Capable of Asymmetric Operation for Wave Energy Converters

Chan Roh
Additional contact information
Chan Roh: Department of Energy Engineering, In-je University, 197 Inje-ro, Gimhae-si 50834, Korea

Energies, 2022, vol. 15, issue 8, 1-21

Abstract: A study on the capacity increase of a power converter according to the increase in the single capacity of wave energy converters and four-leg topology that can supply stable power even under unbalanced load conditions during independent operation is required. Therefore, in this paper, the performances of various four-leg inverters, from two-level inverters to three-level inverters, which are used as power converters for wave energy converters, are compared respectively. Since the four-leg converter has an unusual structure, the performance of each four-leg inverter was analyzed by applying the model predictive control that can easily and simply configure the controller. To verify the performance of each four-leg inverter, a comparison was performed under balanced load and unbalanced load conditions. Based on this, a suitable four-leg topology of the power converter for wave energy converters was confirmed.

Keywords: four-leg inverter; model predictive control; balanced load; unbalanced load; wave energy converter (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 references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/8/2839/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/8/2839/ (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:8:p:2839-:d:792975

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 ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2839-:d:792975