<p>Solar energy, owing to its abundance and renewability, has emerged as a pivotal contributor to long-term energy sustainability and grid resilience. Solar inverter acts as a bridge between photovoltaic systems and the utility grid. The review beings by identifying two core challenges: the evolving complexity of solar inverter topologies and the growing need for improved grid integration. It systematically examines inverter configurations developed to meet five critical grid standards, revealing persistent limitations in control precision, dynamic stability, and scalability. To address these shortcomings, FACTS devices are analysed as complementary technologies, offering enhanced control capabilities and improved power quality features. While the theoretical integration of solar inverters with FACTS devices show promise in strengthening grid coordination and power quality, real-time implementation exposes several practical limitations. To address the identified challenges through sophisticated strategies, the study transitions into a simulation-driven investigation of a novel solar-UPQC configuration. The system incorporates an Adaptive Neuro-Fuzzy Inference System controller optimized via the Gravitational Search Algorithm. This intelligent-metaheuristic control framework enhances the system’s responsiveness to grid disturbances, thereby improving resilience and power quality. The model’s performance is validated through MATLAB/Simulink simulation under diverse grid issues scenario. Results demonstrate marked improvements in voltage regulation, grid stability, and achieve total harmonic distortion below 2%, ensuring compliance with established power quality standards. This phase aims to evaluate the system’s performance in overcoming economic barriers by quantifying its operational effectiveness. The simulation provides detailed insights into how the proposed hybrid system responds to grid disturbance; improve power quality and supports adaptive control under real-world.</p> Graphical Abstract <p></p>