Model predictive control–based virtual synchronous generator for enhanced grid integration under weak grid conditions using adaptive dynamic approach

Purpose This study aims to improve the stability, resilience and power quality of inverter-based resources operating under weak grid conditions by developing a Model Predictive Control–based Virtual Synchronous Generator (MPC-VSG). The scope of this work is limited to passenger car–sized microgrid testbeds, where inverters emulate synchronous generator dynamics to regulate frequency, voltage and power. Design/methodology/approach The proposed MPC-VSG integrates adaptive virtual inertia and damping, adaptive virtual impedance and an active power decoupling mechanism. A comprehensive state-space model is developed, stability is assessed through Lyapunov analysis and the controller is implemented and validated on an OPAL-RT hardware-in-the-loop platform. Comparative evaluations are carried out against conventional VSG and PI-based control schemes across different short-circuit ratios and disturbance scenarios. Findings Hardware-in-the-loop results demonstrate significant performance improvements. Frequency regulation is enhanced by 65%, with deviations constrained to ±0.02 Hz under normal conditions and ±0.04 Hz during severe disturbances, compared to ±0.05 Hz and ±0.1 Hz for traditional VSGs. Active power oscillations are reduced by 58% to ±5%, while reactive power fluctuations decrease by 50% to ±0.1 kVAr. Voltage recovery following a 25% sag is improved by 44%, with recovery time reduced from 450 to 250 ms. The system maintains stable operation under extremely weak grid conditions (Short-Circuit Ratio = 1.5), achieving a 70% reduction in voltage variations and 45% faster transient recovery. Originality/value This research advances Virtual Synchronous Generator (VSG) technology by integrating model predictive control with adaptive parameter tuning algorithms, enhanced power decoupling strategies and predictive fault ride-through mechanisms. The approach enables reliable grid-connected renewable energy integration under challenging weak grid conditions where traditional VSG methods fail to maintain stability, establishing new performance benchmarks for utility-scale renewable energy installations and distributed generation systems.