The increased penetration of Distributed Energy Resources (DERs), including rooftop solar, wind turbines and battery energy storage systems, presents great challenges and opportunities to contemporary power distribution networks. The advanced distributed resources (DERs) often challenge traditional distribution automation (DA) systems with limited capabilities to offer the dynamic bidirectional power flows and stochastic behavior. It has been proposed that the control of distribution automation and the distributed energy access be optimized in a coordinated manner in order to increase the stability, reliability, and efficiency of the grid. Multi-layered architecture is constructed so that it incorporates real-time voltage control, intelligent feeder reconfiguration, and DER dispatch coordination. The suggested optimization model is the Mixed-Integer Linear Programming (MILP) based optimization formulation with Reinforcement Learning (RL) method of adaptive control under different grid conditions. MATLAB/Simulink and Simscape Power Systems is a simulation environment that uses realistic load profiles; solar irradiance data and inverter dynamics. The quantitative outcomes also indicate that the coordinated scheme can minimize the voltage deviation by 41.3% and enhance the DER utilisation by 26.7% and improve the overall amount of energy losses by 17.9% when compared to traditional DA techniques. In addition, regarding contingency reconfiguration scenarios, the RLS-enhanced strategy exhibits a 12.4% more rapid convergence. These results validate the fact that synchronized optimization of DA and DERs does not only stabilize the voltage and frequency, but also has the ability to create an intelligent resilient distribution network. The offered framework proves the feasibility of scaling toward the smart distribution networks amid the decentralization of energy resources and carbon-free electrification.