As energy demand surges due to technological advancements and population growth, optimizing energy supply networks becomes critical. This study presents a novel approach to intelligent energy management in microgrids that incorporates renewable resources and electric vehicle (EV) charging stations. The primary innovation lies in the simultaneous application of the Firefly algorithm and Monte Carlo method to enhance optimization speed and reduce operational costs, a strategy not previously explored in the literature. Despite existing research on microgrid management, significant gaps remain, particularly regarding the integration of EV charging infrastructure without active vehicle participation and the use of fuel cells as energy storage solutions. This paper addresses these gaps by proposing a framework that allows for future consumer integration while minimizing risks associated with operational uncertainties. Key findings indicate that utilizing the Firefly algorithm significantly outperforms traditional Particle Swarm Optimization (PSO) methods in identifying optimal solutions for energy management. The results demonstrate a marked reduction in operational costs over a 24-hour period while ensuring reliability in energy supply. Furthermore, the study establishes a robust foundation for transforming passive distribution systems into active ones, aligning with smart grid concepts
