DOAJ Open Access 2025

High-Performance Tuning for Model Predictive Control for a Renewable Energy Grid-Interface Converter With LCL Filter

Jefferson S. Costa Angelo Lunardi Alessio Iovine Darlan Alexandria Fernandes Daniel Albiero +1 lainnya

Abstrak

Model predictive control (MPC) has emerged as a highly regarded control strategy in power electronics for renewable energy applications. While it minimizes tracking errors and control effort, a significant challenge is the lack of systematic tuning strategies to meet these systems’ energy quality performance requirements. This paper proposes a comprehensive MPC tuning methodology for grid-integrating converters with LCL filters, incorporating modulation and delay compensation. We conduct a stability analysis to define precise constraints for cost function weights. The fine-tuning strategy systematically maps a Figure of Merit (FoM) for system performance using an advanced computational model, revealing that optimal tunings reside in narrow parameter regions. Experimental validation on a 2 kW workbench confirmed that all proposed MPC tunings met IEEE Std. 519-2014 power quality criteria and consistently outperformed a two-sample deadbeat controller, exhibiting enhanced dynamic response and power quality.

Topik & Kata Kunci

Electrical engineering. Electronics. Nuclear engineering

Penulis (6)

Jefferson S. Costa

Angelo Lunardi

Alessio Iovine

Darlan Alexandria Fernandes

Daniel Albiero

Alfeu J. Sguarezi Filho

Format Sitasi

APA MLA BibTeX

Costa, J.S., Lunardi, A., Iovine, A., Fernandes, D.A., Albiero, D., Filho, A.J.S. (2025). High-Performance Tuning for Model Predictive Control for a Renewable Energy Grid-Interface Converter With LCL Filter. https://doi.org/10.1109/ACCESS.2025.3603336

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Informasi Jurnal

Tahun Terbit: 2025
Sumber Database: DOAJ
DOI: 10.1109/ACCESS.2025.3603336
Akses: Open Access ✓