The rapid transition toward sustainable energy systems and climate-neutral infrastructure has significantly accelerated the deployment of Distributed Generation (DG) technologies across modern smart grids. Despite the environmental and economic advantages of renewable energy integration, the increasing penetration of solar photovoltaic systems, wind energy plants, battery storage units, and electric vehicle charging infrastructure has introduced critical Power Quality (PQ) challenges in weak and non-stiff distribution networks. These challenges include voltage instability, harmonic distortion, reactive power imbalance, frequency deviations, and dynamic load fluctuations that adversely affect grid reliability and operational efficiency. This research proposes an intelligent and unified 2026 framework integrating advanced power electronics, artificial intelligence, and adaptive smart-grid control mechanisms for efficient power quality enhancement. An AI-enabled Adaptive Distribution Static Compensator (D-STATCOM) architecture is developed to perform real-time monitoring, predictive harmonic compensation, and autonomous voltage regulation under rapidly changing renewable energy conditions. The proposed system employs machine learning-based predictive control algorithms to mitigate EV-induced transient disturbances, stabilize grid performance, and optimize renewable energy hosting capacity in smart distribution systems. Furthermore, the framework aligns with emerging renewable energy regulations, carbon neutrality targets, Renewable Purchase Obligation (RPO) policies, and international carbon credit mechanisms supporting sustainable energy transformation. Simulation and analytical evaluations demonstrate that the proposed AI-assisted D-STATCOM model effectively minimizes Total Harmonic Distortion (THD), improves voltage stability, enhances power factor correction, and increases renewable energy penetration capability within distribution networks. The results indicate a substantial reduction of harmonic distortion by approximately 92% while improving renewable hosting capability by nearly 40%, thereby contributing toward resilient, intelligent, and environmentally sustainable power systems for next-generation smart grids.