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

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.

# Electrical engineering. Electronics. Nuclear engineering # Grid-connected inverter # model predictive control (MPC) # LCL filter # renewable energy sources (RES) # stability

Jefferson S. Costa, Angelo Lunardi, Alessio Iovine, et al. (2025). "High-Performance Tuning for Model Predictive Control for a Renewable Energy Grid-Interface Converter With LCL Filter". IEEE Access. https://doi.org/10.1109/access.2025.3603336