Significant issues have been brought about by the growing integration of distributed energy resources (DERs) into contemporary power systems, especially in imbalanced networks that are susceptible to a variety of disruptions. under order to improve the disruption-resilience of distributed generation (DG) systems functioning under unbalanced grid situations, this article offers a thorough foundation for intelligent conversion approaches. The suggested method guarantees dependable power supply and system stability during dynamic disturbances including voltage sags, phase imbalances, and line failures by using adaptive control algorithms, machine learning-based fault detection, and real-time voltage balancing mechanisms. The converter architecture's efficacy in reducing power quality deterioration, preserving synchronisation, and guaranteeing quick recovery without sacrificing efficiency is shown by simulation and hardware-in-the-loop validation. An important step towards the development of smarter, more resilient distributed energy systems that can meet the changing needs of decentralised power grids is the integration of intelligent decision-making with strong power electronic interfaces.

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