LAPSE:2023.26023
Published Article
LAPSE:2023.26023
An Integration Optimization Strategy of Line Voltage Cascaded Quasi-Z-Source Inverter Parameters Based on GRA-FA
Zhiyong Li, Shiping Pu, Yougen Chen, Renyong Wei
March 31, 2023
Setting reasonable circuit parameters is an important way to improve the quality of inverters, including waveform quality and power loss. In this paper, a circuit system of line voltage cascaded quasi-Z-source inverter (LVC-qZSI) is built. On this basis, the double frequency voltage ripple ratio and power loss ratio are selected as optimization targets to establish a multi-objective optimization model of LVC-qZSI parameters. To simplify the calculation, an integration optimization strategy of LVC-qZSI parameters based on GRA-FA is proposed. Where, the grey relation analysis (GRA) is used to simplify the multi-objective optimization model. In GRA, the main influence factors are selected as optimization variables by considering the preference coefficient. Then, firefly algorithm (FA) is used to obtain the optimal solution of the multi-objective optimization model. In FA, the weights of objective functions are assigned based on the principle of information entropy. The analysis results are verified by simulation. Research results indicate that the optimization strategy can effectively reduce the double frequency voltage ripple ratio and power loss ratio. Therefore, the strategy proposed in this paper has a superior ability to optimize the parameters of LVC-qZSI, which is of great significance to the initial values setting.
Keywords
double frequency ripple, GRA-FA, LVC-qZSI, parameter optimization, power loss
Suggested Citation
Li Z, Pu S, Chen Y, Wei R. An Integration Optimization Strategy of Line Voltage Cascaded Quasi-Z-Source Inverter Parameters Based on GRA-FA. (2023). LAPSE:2023.26023
Author Affiliations
Li Z: School of Automation, Central South University, 932 South Lushan Road, Changsha 410083, China
Pu S: School of Automation, Central South University, 932 South Lushan Road, Changsha 410083, China [ORCID]
Chen Y: School of Automation, Central South University, 932 South Lushan Road, Changsha 410083, China
Wei R: School of Automation, Central South University, 932 South Lushan Road, Changsha 410083, China
Journal Name
Energies
Volume
13
Issue
17
Article Number
E4391
Year
2020
Publication Date
2020-08-26
ISSN
1996-1073
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PII: en13174391, Publication Type: Journal Article
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https://doi.org/10.3390/en13174391
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