This project presents an ANN-LM–based control strategy for a solar Photovoltaic (PV) system integrated into a Low Voltage Direct Current (LVDC) nano-grid. The system is designed to support electrification in urban residential buildings, remote rural communities, and to strengthen existing grid infrastructure. The core objective is to implement an Artificial Neural Network (ANN) using the Levenberg–Marquardt (LM) algorithm for Maximum Power Point Tracking (MPPT). The study explores effective control and power management strategies among the components of the LVDC nano-grid. The proposed LVDC nano-grid model is developed in MATLAB/Simulink and incorporates an ANN-LM–based MPPT controller. Extensive simulation studies are performed to evaluate the performance of the system under various operating conditions. Additionally, a reliability assessment of the LVDC nano-grid with the proposed controller is conducted, demonstrating its feasibility and potential economic benefits. The results show that integrating advanced control strategies and the ANN-LM MPPT algorithm significantly improves the reliability and efficiency of the LVDC nano-grid, making it a promising solution for sustainable energy distribution across diverse applications.