A Sustainable Methodology to Energy Administration and Cost Reduction approach

To address the challenges of integrating clean power resources and evolving microgrid technologies, new energy control methods are essential. This work introduces Fuzzy Logic-Based Particle Swarm Optimization (FLPSO) for enhancing the efficiency of hybrid energy systems. FLPSO improves convergence rates and solution precision while maintaining resilience to complex conditions. By utilizing fuzzy logic to dynamically adjust PSO variables, it optimizes the distribution and consumption of diverse power sources in a grid-connected microgrid. Results show FLPSO reduces electrical power and battery replacement costs significantly compared to conventional PSO, saving ₹19,596.30 in fixed utility charges and ₹19,691.26 under flexible grid rates. Despite the challenges of battery deterioration, FLPSO outperforms PSO with enhanced sustainability, faster convergence, and lower operating costs, making it a more robust solution for energy management. Keywords: Microgrid Technologies, Fuzzy Logic-Built Particle Swarm Optimizations (FLPSO), Hybrid Systems for Energy Administration, Optimization Challenges, Battery Storages Deterioration, System Fluctuations.